import pandas as pd
import os, pickle
import numpy as np
import pymongo
import sys
sys.path.append('../')
import src.IQ as IQ
myclient = pymongo.MongoClient("mongodb://127.0.0.1:27017/admin")
BLE = myclient["BLE"]
def query(collection, filter:dict, addFrameColumn=True):
df = pd.DataFrame(list(collection.find(filter)))
if addFrameColumn:
df['frame'] = df.apply(lambda x: x['I'] + np.dot(x['Q'],1j), axis=1)
return df.copy()
from tensorflow.keras.models import Model
from tensorflow.keras.layers import Input, Dense
from tensorflow.keras.optimizers import Adam
import tensorflow as tf
import matplotlib.pyplot as plt
from tensorflow.keras.callbacks import EarlyStopping
from sklearn.preprocessing import StandardScaler
from tensorflow.keras.backend import clear_session
from tensorflow.keras.regularizers import l1, l2
import threading
from sklearn.preprocessing import MinMaxScaler
# We will start with a size that is approximately half of the input size
def run(encoding_dim,input_tensor_features,output_tensor_features, plot = False):
tf.keras.backend.clear_session()
input_shape = input_tensor_features[0].shape[0]
output_shape = output_tensor_features[0].shape[0]
input_data = Input(shape=(input_shape,))
encoded = Dense(encoding_dim + (input_shape - encoding_dim )//2, activation='relu')(input_data)
encoded = Dense(encoding_dim + (input_shape - encoding_dim )//4, activation='tanh')(encoded)
encoded = Dense(encoding_dim, activation='linear')(encoded) # kernel_regularizer=l1(0.01)
decoded = Dense(encoding_dim + (output_shape - encoding_dim )//4, activation='tanh')(encoded)
decoded = Dense(encoding_dim + (output_shape - encoding_dim )//2, activation='relu')(decoded)
decoded = Dense(output_shape, activation='linear')(decoded)
# This model maps an input to its reconstruction
autoencoder = Model(input_data, decoded)
# This model maps an input to its encoded representation
# encoder = Model(input_data, encoded)
# Compile the model
autoencoder.compile(optimizer=Adam(learning_rate=0.001), loss='mean_squared_error')
# Display the architecture of the autoencoder
with lock:
autoencoder.summary()
# Train the autoencoder
# We will use new_csv_features as both the input and the target since it's an autoencoder
early_stopping = EarlyStopping(monitor='val_loss', patience=40, verbose=1)
# Train the autoencoder and save the history
history = autoencoder.fit(input_tensor_features, output_tensor_features,
epochs=2048,
batch_size=16,
shuffle=True,
validation_split=0.2,
callbacks=[early_stopping],
verbose=0,
) # Set verbose to 1 for progress output
best_loss = min(history.history['val_loss']) # this is the raining loss
best_losses[encoding_dim] = best_loss
print("latent dim:", encoding_dim, "loss value is: ", best_loss)
if plot:
lock.acquire()
plt.figure(figsize=(10, 2),dpi=80)
plt.plot(output_tensor_features[199], label='original')
plt.plot(autoencoder(input_tensor_features)[199], label='reconstructed')
plt.title('Latnet dim:'+ str(encoding_dim)+", best loss:"+str(best_loss))
plt.legend()
plt.show()
plt.close()
# plt.figure(figsize=(20, 4))
# for i in range (1,len(autoencoder.layers)-1):
# # Assuming 'autoencoder' is your trained model and 'layer_index' is the index of the layer you want to analyze
# weights = autoencoder.layers[i].get_weights()[0] # 0 for weights, 1 for biases
# # Plotting the weights as a heatmap
# plt.subplot(1,len(autoencoder.layers)-2,i)
# plt.imshow(weights, cmap='viridis', aspect='auto')
# plt.colorbar()
# plt.show()
# plt.close()
# plt.figure(figsize=(10, 16))
# for i in range (1,len(autoencoder.layers)-1):
# # Assuming 'autoencoder' is your trained model and 'layer_index' is the index of the layer you want to analyze
# weights = autoencoder.layers[i].get_weights()[0] # 0 for weights, 1 for biases
# biases = autoencoder.layers[i].get_weights()[1] # 0 for weights, 1 for biases
# # Histogram of the weight values
# plt.subplot(2*(len(autoencoder.layers)-2),1,i*2-1)
# plt.plot(weights.flatten().tolist(), label='weights')
# plt.plot(np.linspace(0,len(weights.flatten()),len(biases.flatten())),biases.flatten().tolist(), label='biases')
# plt.legend()
# plt.subplot(2*(len(autoencoder.layers)-2),2,i*4-1)
# plt.hist(weights.flatten(), bins=50)
# # Histogram of the biases values
# plt.subplot(2*(len(autoencoder.layers)-2),2,i*4)
# plt.hist(biases.flatten(), bins=50)
# plt.show()
# plt.close()
lock.release()
tf.keras.backend.clear_session()
clear_session()
# Create a StandardScaler object
scaler = StandardScaler()
scaler2 = MinMaxScaler(feature_range=(0, 1))
# Assuming 'new_csv_features' is your data
def normalized(row):
row = np.array(row)
return scaler2.fit_transform(scaler.fit_transform(row.reshape(-1, 1)))
def fft_normalized(row):
row = np.array(row)
temp = np.fft.fft(row)[0:len(row)//2 + 1]
amp = normalized(np.abs(temp))
filtering = amp > np.average(amp)*.05
angle = normalized(np.angle(temp))
angle = angle[filtering]
angle = np.concatenate([angle,np.zeros(len(row)-len(angle))])
amp = amp[filtering]
amp = np.concatenate([amp,np.zeros(len(row)-len(amp))])
return np.concatenate([amp,angle])
lock = threading.Lock()
batch_size = 1
filtering = {''}
df = query(BLE['onBody'], {'pos':'static','antenna_side':'left'})
min_length = df['frame'].apply(len).min()
df['frame'] = df['frame'].apply(lambda x: x[:2000])
print(len(df['frame'][0]))
print(type(df['frame'][0]))
iq = IQ.IQ(Fc=2439810000+.1e4)
def configCreator(downSampleRate = 1, cutoff = 1e6):
downSampleRate= max(downSampleRate, 1)
return {
# iq.gradient:{},
iq.unwrapPhase:{},
iq.phase:{},
# iq.butter:{'Fs': iq.Fs/downSampleRate, "cutoff": cutoff},
iq.downSample:{'downSampleRate':downSampleRate, "shift": 0},
iq.demodulate:{'Fs': iq.Fs},
}
methods = configCreator(downSampleRate= 10)
df['data'] = iq.apply(methods = methods, frame = df)
####################################################################################
# df['normalized'] = df['predictor'].apply(lambda x: normalized(x))
df['normalized'] = df['data'].apply(lambda x: fft_normalized(x))
input_tensor_features = tf.convert_to_tensor(df['normalized'].tolist())
df['normalized'] = df['data']#.apply(lambda x: normalized(x))
output_tensor_features = tf.convert_to_tensor(df['normalized'].tolist())
data_shape = len(df['data'][0])
#####################################################################################
best_losses = {}
for batch in range(1,int(np.ceil(data_shape/batch_size))):
try:
run(batch,output_tensor_features,output_tensor_features,True)
except:
continue
# threads = []
# for i in range(batch_size * batch+1, min(batch_size * batch+batch_size+1,data_shape)):
# run, args=(i,output_tensor_features,output_tensor_features,True, )
# threads.append(threading.Thread(target=run, args=(i,output_tensor_features,output_tensor_features,True, )))
# threads[-1].start()
# for t in threads:
# t.join()
best_losses = dict(sorted(best_losses.items()))
lossDF = pd.DataFrame(best_losses.values(),index=best_losses.keys())
lossDF.plot()
lossDF.to_csv('loss.csv')
plt.xlabel('Latent dimension')
plt.ylabel('Best loss')
plt.title('dataset: onBody static left')
plt.savefig('res/'+"onBody static left"+'.png')
plt.show()
plt.close()
2023-11-15 21:46:45.044447: I tensorflow/core/util/port.cc:111] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`. 2023-11-15 21:46:45.067717: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered 2023-11-15 21:46:45.067738: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered 2023-11-15 21:46:45.067754: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered 2023-11-15 21:46:45.071654: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations. To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2000 <class 'numpy.ndarray'>
2023-11-15 21:46:53.076839: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:894] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 2023-11-15 21:46:53.094172: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:894] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 2023-11-15 21:46:53.094629: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:894] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 2023-11-15 21:46:53.099765: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:894] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 2023-11-15 21:46:53.100213: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:894] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 2023-11-15 21:46:53.100554: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:894] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 2023-11-15 21:46:53.525973: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:894] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 2023-11-15 21:46:53.526076: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:894] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 2023-11-15 21:46:53.526148: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:894] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 2023-11-15 21:46:53.526205: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1886] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 4620 MB memory: -> device: 0, name: NVIDIA GeForce RTX 3060 Ti, pci bus id: 0000:01:00.0, compute capability: 8.6
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 100) 20100
dense_1 (Dense) (None, 50) 5050
dense_2 (Dense) (None, 1) 51
dense_3 (Dense) (None, 50) 100
dense_4 (Dense) (None, 100) 5100
dense_5 (Dense) (None, 200) 20200
=================================================================
Total params: 50601 (197.66 KB)
Trainable params: 50601 (197.66 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
2023-11-15 21:46:54.852903: I tensorflow/tsl/platform/default/subprocess.cc:304] Start cannot spawn child process: No such file or directory 2023-11-15 21:46:55.182067: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f2ff401ea20 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2023-11-15 21:46:55.182091: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 3060 Ti, Compute Capability 8.6 2023-11-15 21:46:55.187073: I tensorflow/compiler/mlir/tensorflow/utils/dump_mlir_util.cc:269] disabling MLIR crash reproducer, set env var `MLIR_CRASH_REPRODUCER_DIRECTORY` to enable. 2023-11-15 21:46:55.357198: I tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:442] Loaded cuDNN version 8700 2023-11-15 21:46:55.436993: I ./tensorflow/compiler/jit/device_compiler.h:186] Compiled cluster using XLA! This line is logged at most once for the lifetime of the process.
Epoch 80: early stopping latent dim: 1 loss value is: 0.3288440704345703
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 101) 20301
dense_1 (Dense) (None, 51) 5202
dense_2 (Dense) (None, 2) 104
dense_3 (Dense) (None, 51) 153
dense_4 (Dense) (None, 101) 5252
dense_5 (Dense) (None, 200) 20400
=================================================================
Total params: 51412 (200.83 KB)
Trainable params: 51412 (200.83 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 73: early stopping
latent dim: 2 loss value is: 0.0939439907670021
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 101) 20301
dense_1 (Dense) (None, 52) 5304
dense_2 (Dense) (None, 3) 159
dense_3 (Dense) (None, 52) 208
dense_4 (Dense) (None, 101) 5353
dense_5 (Dense) (None, 200) 20400
=================================================================
Total params: 51725 (202.05 KB)
Trainable params: 51725 (202.05 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 197: early stopping
latent dim: 3 loss value is: 0.03543655574321747
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 102) 20502
dense_1 (Dense) (None, 53) 5459
dense_2 (Dense) (None, 4) 216
dense_3 (Dense) (None, 53) 265
dense_4 (Dense) (None, 102) 5508
dense_5 (Dense) (None, 200) 20600
=================================================================
Total params: 52550 (205.27 KB)
Trainable params: 52550 (205.27 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 81: early stopping
latent dim: 4 loss value is: 0.06580591201782227
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 102) 20502
dense_1 (Dense) (None, 53) 5459
dense_2 (Dense) (None, 5) 270
dense_3 (Dense) (None, 53) 318
dense_4 (Dense) (None, 102) 5508
dense_5 (Dense) (None, 200) 20600
=================================================================
Total params: 52657 (205.69 KB)
Trainable params: 52657 (205.69 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 112: early stopping
latent dim: 5 loss value is: 0.040589649230241776
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 103) 20703
dense_1 (Dense) (None, 54) 5616
dense_2 (Dense) (None, 6) 330
dense_3 (Dense) (None, 54) 378
dense_4 (Dense) (None, 103) 5665
dense_5 (Dense) (None, 200) 20800
=================================================================
Total params: 53492 (208.95 KB)
Trainable params: 53492 (208.95 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 93: early stopping
latent dim: 6 loss value is: 0.042531322687864304
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 103) 20703
dense_1 (Dense) (None, 55) 5720
dense_2 (Dense) (None, 7) 392
dense_3 (Dense) (None, 55) 440
dense_4 (Dense) (None, 103) 5768
dense_5 (Dense) (None, 200) 20800
=================================================================
Total params: 53823 (210.25 KB)
Trainable params: 53823 (210.25 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 68: early stopping
latent dim: 7 loss value is: 0.052858173847198486
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 104) 20904
dense_1 (Dense) (None, 56) 5880
dense_2 (Dense) (None, 8) 456
dense_3 (Dense) (None, 56) 504
dense_4 (Dense) (None, 104) 5928
dense_5 (Dense) (None, 200) 21000
=================================================================
Total params: 54672 (213.56 KB)
Trainable params: 54672 (213.56 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 98: early stopping
latent dim: 8 loss value is: 0.03358779475092888
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 104) 20904
dense_1 (Dense) (None, 56) 5880
dense_2 (Dense) (None, 9) 513
dense_3 (Dense) (None, 56) 560
dense_4 (Dense) (None, 104) 5928
dense_5 (Dense) (None, 200) 21000
=================================================================
Total params: 54785 (214.00 KB)
Trainable params: 54785 (214.00 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 73: early stopping
latent dim: 9 loss value is: 0.045272860676050186
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 105) 21105
dense_1 (Dense) (None, 57) 6042
dense_2 (Dense) (None, 10) 580
dense_3 (Dense) (None, 57) 627
dense_4 (Dense) (None, 105) 6090
dense_5 (Dense) (None, 200) 21200
=================================================================
Total params: 55644 (217.36 KB)
Trainable params: 55644 (217.36 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 58: early stopping
latent dim: 10 loss value is: 0.05924901366233826
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 105) 21105
dense_1 (Dense) (None, 58) 6148
dense_2 (Dense) (None, 11) 649
dense_3 (Dense) (None, 58) 696
dense_4 (Dense) (None, 105) 6195
dense_5 (Dense) (None, 200) 21200
=================================================================
Total params: 55993 (218.72 KB)
Trainable params: 55993 (218.72 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 87: early stopping
latent dim: 11 loss value is: 0.04655012488365173
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 106) 21306
dense_1 (Dense) (None, 59) 6313
dense_2 (Dense) (None, 12) 720
dense_3 (Dense) (None, 59) 767
dense_4 (Dense) (None, 106) 6360
dense_5 (Dense) (None, 200) 21400
=================================================================
Total params: 56866 (222.13 KB)
Trainable params: 56866 (222.13 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 164: early stopping
latent dim: 12 loss value is: 0.03800926357507706
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 106) 21306
dense_1 (Dense) (None, 59) 6313
dense_2 (Dense) (None, 13) 780
dense_3 (Dense) (None, 59) 826
dense_4 (Dense) (None, 106) 6360
dense_5 (Dense) (None, 200) 21400
=================================================================
Total params: 56985 (222.60 KB)
Trainable params: 56985 (222.60 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 126: early stopping
latent dim: 13 loss value is: 0.03565207123756409
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 107) 21507
dense_1 (Dense) (None, 60) 6480
dense_2 (Dense) (None, 14) 854
dense_3 (Dense) (None, 60) 900
dense_4 (Dense) (None, 107) 6527
dense_5 (Dense) (None, 200) 21600
=================================================================
Total params: 57868 (226.05 KB)
Trainable params: 57868 (226.05 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 123: early stopping
latent dim: 14 loss value is: 0.04052715748548508
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 107) 21507
dense_1 (Dense) (None, 61) 6588
dense_2 (Dense) (None, 15) 930
dense_3 (Dense) (None, 61) 976
dense_4 (Dense) (None, 107) 6634
dense_5 (Dense) (None, 200) 21600
=================================================================
Total params: 58235 (227.48 KB)
Trainable params: 58235 (227.48 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 104: early stopping
latent dim: 15 loss value is: 0.04415132477879524
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 108) 21708
dense_1 (Dense) (None, 62) 6758
dense_2 (Dense) (None, 16) 1008
dense_3 (Dense) (None, 62) 1054
dense_4 (Dense) (None, 108) 6804
dense_5 (Dense) (None, 200) 21800
=================================================================
Total params: 59132 (230.98 KB)
Trainable params: 59132 (230.98 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 61: early stopping
latent dim: 16 loss value is: 0.05921231582760811
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 108) 21708
dense_1 (Dense) (None, 62) 6758
dense_2 (Dense) (None, 17) 1071
dense_3 (Dense) (None, 62) 1116
dense_4 (Dense) (None, 108) 6804
dense_5 (Dense) (None, 200) 21800
=================================================================
Total params: 59257 (231.47 KB)
Trainable params: 59257 (231.47 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 148: early stopping
latent dim: 17 loss value is: 0.034773703664541245
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 109) 21909
dense_1 (Dense) (None, 63) 6930
dense_2 (Dense) (None, 18) 1152
dense_3 (Dense) (None, 63) 1197
dense_4 (Dense) (None, 109) 6976
dense_5 (Dense) (None, 200) 22000
=================================================================
Total params: 60164 (235.02 KB)
Trainable params: 60164 (235.02 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 156: early stopping
latent dim: 18 loss value is: 0.030283845961093903
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 109) 21909
dense_1 (Dense) (None, 64) 7040
dense_2 (Dense) (None, 19) 1235
dense_3 (Dense) (None, 64) 1280
dense_4 (Dense) (None, 109) 7085
dense_5 (Dense) (None, 200) 22000
=================================================================
Total params: 60549 (236.52 KB)
Trainable params: 60549 (236.52 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 69: early stopping
latent dim: 19 loss value is: 0.044518619775772095
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 110) 22110
dense_1 (Dense) (None, 65) 7215
dense_2 (Dense) (None, 20) 1320
dense_3 (Dense) (None, 65) 1365
dense_4 (Dense) (None, 110) 7260
dense_5 (Dense) (None, 200) 22200
=================================================================
Total params: 61470 (240.12 KB)
Trainable params: 61470 (240.12 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 92: early stopping
latent dim: 20 loss value is: 0.05410527065396309
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 110) 22110
dense_1 (Dense) (None, 65) 7215
dense_2 (Dense) (None, 21) 1386
dense_3 (Dense) (None, 65) 1430
dense_4 (Dense) (None, 110) 7260
dense_5 (Dense) (None, 200) 22200
=================================================================
Total params: 61601 (240.63 KB)
Trainable params: 61601 (240.63 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 59: early stopping
latent dim: 21 loss value is: 0.05669870972633362
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 111) 22311
dense_1 (Dense) (None, 66) 7392
dense_2 (Dense) (None, 22) 1474
dense_3 (Dense) (None, 66) 1518
dense_4 (Dense) (None, 111) 7437
dense_5 (Dense) (None, 200) 22400
=================================================================
Total params: 62532 (244.27 KB)
Trainable params: 62532 (244.27 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 70: early stopping
latent dim: 22 loss value is: 0.045616548508405685
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 111) 22311
dense_1 (Dense) (None, 67) 7504
dense_2 (Dense) (None, 23) 1564
dense_3 (Dense) (None, 67) 1608
dense_4 (Dense) (None, 111) 7548
dense_5 (Dense) (None, 200) 22400
=================================================================
Total params: 62935 (245.84 KB)
Trainable params: 62935 (245.84 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 72: early stopping
latent dim: 23 loss value is: 0.051304351538419724
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 112) 22512
dense_1 (Dense) (None, 68) 7684
dense_2 (Dense) (None, 24) 1656
dense_3 (Dense) (None, 68) 1700
dense_4 (Dense) (None, 112) 7728
dense_5 (Dense) (None, 200) 22600
=================================================================
Total params: 63880 (249.53 KB)
Trainable params: 63880 (249.53 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 94: early stopping
latent dim: 24 loss value is: 0.05157236009836197
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 112) 22512
dense_1 (Dense) (None, 68) 7684
dense_2 (Dense) (None, 25) 1725
dense_3 (Dense) (None, 68) 1768
dense_4 (Dense) (None, 112) 7728
dense_5 (Dense) (None, 200) 22600
=================================================================
Total params: 64017 (250.07 KB)
Trainable params: 64017 (250.07 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 245: early stopping
latent dim: 25 loss value is: 0.023938454687595367
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 113) 22713
dense_1 (Dense) (None, 69) 7866
dense_2 (Dense) (None, 26) 1820
dense_3 (Dense) (None, 69) 1863
dense_4 (Dense) (None, 113) 7910
dense_5 (Dense) (None, 200) 22800
=================================================================
Total params: 64972 (253.80 KB)
Trainable params: 64972 (253.80 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 111: early stopping
latent dim: 26 loss value is: 0.03703451529145241
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 113) 22713
dense_1 (Dense) (None, 70) 7980
dense_2 (Dense) (None, 27) 1917
dense_3 (Dense) (None, 70) 1960
dense_4 (Dense) (None, 113) 8023
dense_5 (Dense) (None, 200) 22800
=================================================================
Total params: 65393 (255.44 KB)
Trainable params: 65393 (255.44 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 105: early stopping
latent dim: 27 loss value is: 0.03875560685992241
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 114) 22914
dense_1 (Dense) (None, 71) 8165
dense_2 (Dense) (None, 28) 2016
dense_3 (Dense) (None, 71) 2059
dense_4 (Dense) (None, 114) 8208
dense_5 (Dense) (None, 200) 23000
=================================================================
Total params: 66362 (259.23 KB)
Trainable params: 66362 (259.23 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 56: early stopping
latent dim: 28 loss value is: 0.049135975539684296
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 114) 22914
dense_1 (Dense) (None, 71) 8165
dense_2 (Dense) (None, 29) 2088
dense_3 (Dense) (None, 71) 2130
dense_4 (Dense) (None, 114) 8208
dense_5 (Dense) (None, 200) 23000
=================================================================
Total params: 66505 (259.79 KB)
Trainable params: 66505 (259.79 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 69: early stopping
latent dim: 29 loss value is: 0.043004535138607025
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 115) 23115
dense_1 (Dense) (None, 72) 8352
dense_2 (Dense) (None, 30) 2190
dense_3 (Dense) (None, 72) 2232
dense_4 (Dense) (None, 115) 8395
dense_5 (Dense) (None, 200) 23200
=================================================================
Total params: 67484 (263.61 KB)
Trainable params: 67484 (263.61 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 130: early stopping
latent dim: 30 loss value is: 0.034749455749988556
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 115) 23115
dense_1 (Dense) (None, 73) 8468
dense_2 (Dense) (None, 31) 2294
dense_3 (Dense) (None, 73) 2336
dense_4 (Dense) (None, 115) 8510
dense_5 (Dense) (None, 200) 23200
=================================================================
Total params: 67923 (265.32 KB)
Trainable params: 67923 (265.32 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 81: early stopping
latent dim: 31 loss value is: 0.046769045293331146
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 116) 23316
dense_1 (Dense) (None, 74) 8658
dense_2 (Dense) (None, 32) 2400
dense_3 (Dense) (None, 74) 2442
dense_4 (Dense) (None, 116) 8700
dense_5 (Dense) (None, 200) 23400
=================================================================
Total params: 68916 (269.20 KB)
Trainable params: 68916 (269.20 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 86: early stopping
latent dim: 32 loss value is: 0.04814862087368965
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 116) 23316
dense_1 (Dense) (None, 74) 8658
dense_2 (Dense) (None, 33) 2475
dense_3 (Dense) (None, 74) 2516
dense_4 (Dense) (None, 116) 8700
dense_5 (Dense) (None, 200) 23400
=================================================================
Total params: 69065 (269.79 KB)
Trainable params: 69065 (269.79 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 126: early stopping
latent dim: 33 loss value is: 0.0447305329144001
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 117) 23517
dense_1 (Dense) (None, 75) 8850
dense_2 (Dense) (None, 34) 2584
dense_3 (Dense) (None, 75) 2625
dense_4 (Dense) (None, 117) 8892
dense_5 (Dense) (None, 200) 23600
=================================================================
Total params: 70068 (273.70 KB)
Trainable params: 70068 (273.70 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 91: early stopping
latent dim: 34 loss value is: 0.04011492058634758
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 117) 23517
dense_1 (Dense) (None, 76) 8968
dense_2 (Dense) (None, 35) 2695
dense_3 (Dense) (None, 76) 2736
dense_4 (Dense) (None, 117) 9009
dense_5 (Dense) (None, 200) 23600
=================================================================
Total params: 70525 (275.49 KB)
Trainable params: 70525 (275.49 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 129: early stopping
latent dim: 35 loss value is: 0.041482310742139816
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 118) 23718
dense_1 (Dense) (None, 77) 9163
dense_2 (Dense) (None, 36) 2808
dense_3 (Dense) (None, 77) 2849
dense_4 (Dense) (None, 118) 9204
dense_5 (Dense) (None, 200) 23800
=================================================================
Total params: 71542 (279.46 KB)
Trainable params: 71542 (279.46 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 64: early stopping
latent dim: 36 loss value is: 0.04714420065283775
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 118) 23718
dense_1 (Dense) (None, 77) 9163
dense_2 (Dense) (None, 37) 2886
dense_3 (Dense) (None, 77) 2926
dense_4 (Dense) (None, 118) 9204
dense_5 (Dense) (None, 200) 23800
=================================================================
Total params: 71697 (280.07 KB)
Trainable params: 71697 (280.07 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 62: early stopping
latent dim: 37 loss value is: 0.049341339617967606
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 119) 23919
dense_1 (Dense) (None, 78) 9360
dense_2 (Dense) (None, 38) 3002
dense_3 (Dense) (None, 78) 3042
dense_4 (Dense) (None, 119) 9401
dense_5 (Dense) (None, 200) 24000
=================================================================
Total params: 72724 (284.08 KB)
Trainable params: 72724 (284.08 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 155: early stopping
latent dim: 38 loss value is: 0.03871140256524086
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 119) 23919
dense_1 (Dense) (None, 79) 9480
dense_2 (Dense) (None, 39) 3120
dense_3 (Dense) (None, 79) 3160
dense_4 (Dense) (None, 119) 9520
dense_5 (Dense) (None, 200) 24000
=================================================================
Total params: 73199 (285.93 KB)
Trainable params: 73199 (285.93 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 141: early stopping
latent dim: 39 loss value is: 0.03776484355330467
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 120) 24120
dense_1 (Dense) (None, 80) 9680
dense_2 (Dense) (None, 40) 3240
dense_3 (Dense) (None, 80) 3280
dense_4 (Dense) (None, 120) 9720
dense_5 (Dense) (None, 200) 24200
=================================================================
Total params: 74240 (290.00 KB)
Trainable params: 74240 (290.00 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 71: early stopping
latent dim: 40 loss value is: 0.04450492188334465
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 120) 24120
dense_1 (Dense) (None, 80) 9680
dense_2 (Dense) (None, 41) 3321
dense_3 (Dense) (None, 80) 3360
dense_4 (Dense) (None, 120) 9720
dense_5 (Dense) (None, 200) 24200
=================================================================
Total params: 74401 (290.63 KB)
Trainable params: 74401 (290.63 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 100: early stopping
latent dim: 41 loss value is: 0.044573478400707245
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 121) 24321
dense_1 (Dense) (None, 81) 9882
dense_2 (Dense) (None, 42) 3444
dense_3 (Dense) (None, 81) 3483
dense_4 (Dense) (None, 121) 9922
dense_5 (Dense) (None, 200) 24400
=================================================================
Total params: 75452 (294.73 KB)
Trainable params: 75452 (294.73 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 79: early stopping
latent dim: 42 loss value is: 0.04184245318174362
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 121) 24321
dense_1 (Dense) (None, 82) 10004
dense_2 (Dense) (None, 43) 3569
dense_3 (Dense) (None, 82) 3608
dense_4 (Dense) (None, 121) 10043
dense_5 (Dense) (None, 200) 24400
=================================================================
Total params: 75945 (296.66 KB)
Trainable params: 75945 (296.66 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 68: early stopping
latent dim: 43 loss value is: 0.055189430713653564
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 122) 24522
dense_1 (Dense) (None, 83) 10209
dense_2 (Dense) (None, 44) 3696
dense_3 (Dense) (None, 83) 3735
dense_4 (Dense) (None, 122) 10248
dense_5 (Dense) (None, 200) 24600
=================================================================
Total params: 77010 (300.82 KB)
Trainable params: 77010 (300.82 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 119: early stopping
latent dim: 44 loss value is: 0.02828378975391388
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 122) 24522
dense_1 (Dense) (None, 83) 10209
dense_2 (Dense) (None, 45) 3780
dense_3 (Dense) (None, 83) 3818
dense_4 (Dense) (None, 122) 10248
dense_5 (Dense) (None, 200) 24600
=================================================================
Total params: 77177 (301.47 KB)
Trainable params: 77177 (301.47 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 83: early stopping
latent dim: 45 loss value is: 0.04031725600361824
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 123) 24723
dense_1 (Dense) (None, 84) 10416
dense_2 (Dense) (None, 46) 3910
dense_3 (Dense) (None, 84) 3948
dense_4 (Dense) (None, 123) 10455
dense_5 (Dense) (None, 200) 24800
=================================================================
Total params: 78252 (305.67 KB)
Trainable params: 78252 (305.67 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 73: early stopping
latent dim: 46 loss value is: 0.047719743102788925
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 123) 24723
dense_1 (Dense) (None, 85) 10540
dense_2 (Dense) (None, 47) 4042
dense_3 (Dense) (None, 85) 4080
dense_4 (Dense) (None, 123) 10578
dense_5 (Dense) (None, 200) 24800
=================================================================
Total params: 78763 (307.67 KB)
Trainable params: 78763 (307.67 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 95: early stopping
latent dim: 47 loss value is: 0.03401003032922745
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 124) 24924
dense_1 (Dense) (None, 86) 10750
dense_2 (Dense) (None, 48) 4176
dense_3 (Dense) (None, 86) 4214
dense_4 (Dense) (None, 124) 10788
dense_5 (Dense) (None, 200) 25000
=================================================================
Total params: 79852 (311.92 KB)
Trainable params: 79852 (311.92 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 172: early stopping
latent dim: 48 loss value is: 0.03502686321735382
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 124) 24924
dense_1 (Dense) (None, 86) 10750
dense_2 (Dense) (None, 49) 4263
dense_3 (Dense) (None, 86) 4300
dense_4 (Dense) (None, 124) 10788
dense_5 (Dense) (None, 200) 25000
=================================================================
Total params: 80025 (312.60 KB)
Trainable params: 80025 (312.60 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 75: early stopping
latent dim: 49 loss value is: 0.03593837469816208
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 125) 25125
dense_1 (Dense) (None, 87) 10962
dense_2 (Dense) (None, 50) 4400
dense_3 (Dense) (None, 87) 4437
dense_4 (Dense) (None, 125) 11000
dense_5 (Dense) (None, 200) 25200
=================================================================
Total params: 81124 (316.89 KB)
Trainable params: 81124 (316.89 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 65: early stopping
latent dim: 50 loss value is: 0.04781133309006691
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 125) 25125
dense_1 (Dense) (None, 88) 11088
dense_2 (Dense) (None, 51) 4539
dense_3 (Dense) (None, 88) 4576
dense_4 (Dense) (None, 125) 11125
dense_5 (Dense) (None, 200) 25200
=================================================================
Total params: 81653 (318.96 KB)
Trainable params: 81653 (318.96 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 92: early stopping
latent dim: 51 loss value is: 0.03563827648758888
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 126) 25326
dense_1 (Dense) (None, 89) 11303
dense_2 (Dense) (None, 52) 4680
dense_3 (Dense) (None, 89) 4717
dense_4 (Dense) (None, 126) 11340
dense_5 (Dense) (None, 200) 25400
=================================================================
Total params: 82766 (323.30 KB)
Trainable params: 82766 (323.30 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 72: early stopping
latent dim: 52 loss value is: 0.04657257720828056
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 126) 25326
dense_1 (Dense) (None, 89) 11303
dense_2 (Dense) (None, 53) 4770
dense_3 (Dense) (None, 89) 4806
dense_4 (Dense) (None, 126) 11340
dense_5 (Dense) (None, 200) 25400
=================================================================
Total params: 82945 (324.00 KB)
Trainable params: 82945 (324.00 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 144: early stopping
latent dim: 53 loss value is: 0.03907390311360359
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 127) 25527
dense_1 (Dense) (None, 90) 11520
dense_2 (Dense) (None, 54) 4914
dense_3 (Dense) (None, 90) 4950
dense_4 (Dense) (None, 127) 11557
dense_5 (Dense) (None, 200) 25600
=================================================================
Total params: 84068 (328.39 KB)
Trainable params: 84068 (328.39 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 68: early stopping
latent dim: 54 loss value is: 0.048028942197561264
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 127) 25527
dense_1 (Dense) (None, 91) 11648
dense_2 (Dense) (None, 55) 5060
dense_3 (Dense) (None, 91) 5096
dense_4 (Dense) (None, 127) 11684
dense_5 (Dense) (None, 200) 25600
=================================================================
Total params: 84615 (330.53 KB)
Trainable params: 84615 (330.53 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 56: early stopping
latent dim: 55 loss value is: 0.0519341304898262
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 128) 25728
dense_1 (Dense) (None, 92) 11868
dense_2 (Dense) (None, 56) 5208
dense_3 (Dense) (None, 92) 5244
dense_4 (Dense) (None, 128) 11904
dense_5 (Dense) (None, 200) 25800
=================================================================
Total params: 85752 (334.97 KB)
Trainable params: 85752 (334.97 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 93: early stopping
latent dim: 56 loss value is: 0.04398111626505852
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 128) 25728
dense_1 (Dense) (None, 92) 11868
dense_2 (Dense) (None, 57) 5301
dense_3 (Dense) (None, 92) 5336
dense_4 (Dense) (None, 128) 11904
dense_5 (Dense) (None, 200) 25800
=================================================================
Total params: 85937 (335.69 KB)
Trainable params: 85937 (335.69 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 113: early stopping
latent dim: 57 loss value is: 0.04077240079641342
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 129) 25929
dense_1 (Dense) (None, 93) 12090
dense_2 (Dense) (None, 58) 5452
dense_3 (Dense) (None, 93) 5487
dense_4 (Dense) (None, 129) 12126
dense_5 (Dense) (None, 200) 26000
=================================================================
Total params: 87084 (340.17 KB)
Trainable params: 87084 (340.17 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 53: early stopping
latent dim: 58 loss value is: 0.045813120901584625
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 129) 25929
dense_1 (Dense) (None, 94) 12220
dense_2 (Dense) (None, 59) 5605
dense_3 (Dense) (None, 94) 5640
dense_4 (Dense) (None, 129) 12255
dense_5 (Dense) (None, 200) 26000
=================================================================
Total params: 87649 (342.38 KB)
Trainable params: 87649 (342.38 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 103: early stopping
latent dim: 59 loss value is: 0.037973083555698395
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 130) 26130
dense_1 (Dense) (None, 95) 12445
dense_2 (Dense) (None, 60) 5760
dense_3 (Dense) (None, 95) 5795
dense_4 (Dense) (None, 130) 12480
dense_5 (Dense) (None, 200) 26200
=================================================================
Total params: 88810 (346.91 KB)
Trainable params: 88810 (346.91 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 104: early stopping
latent dim: 60 loss value is: 0.03608359768986702
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 130) 26130
dense_1 (Dense) (None, 95) 12445
dense_2 (Dense) (None, 61) 5856
dense_3 (Dense) (None, 95) 5890
dense_4 (Dense) (None, 130) 12480
dense_5 (Dense) (None, 200) 26200
=================================================================
Total params: 89001 (347.66 KB)
Trainable params: 89001 (347.66 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 66: early stopping
latent dim: 61 loss value is: 0.03608286753296852
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 131) 26331
dense_1 (Dense) (None, 96) 12672
dense_2 (Dense) (None, 62) 6014
dense_3 (Dense) (None, 96) 6048
dense_4 (Dense) (None, 131) 12707
dense_5 (Dense) (None, 200) 26400
=================================================================
Total params: 90172 (352.23 KB)
Trainable params: 90172 (352.23 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 245: early stopping
latent dim: 62 loss value is: 0.03907230496406555
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 131) 26331
dense_1 (Dense) (None, 97) 12804
dense_2 (Dense) (None, 63) 6174
dense_3 (Dense) (None, 97) 6208
dense_4 (Dense) (None, 131) 12838
dense_5 (Dense) (None, 200) 26400
=================================================================
Total params: 90755 (354.51 KB)
Trainable params: 90755 (354.51 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 49: early stopping
latent dim: 63 loss value is: 0.048331551253795624
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 132) 26532
dense_1 (Dense) (None, 98) 13034
dense_2 (Dense) (None, 64) 6336
dense_3 (Dense) (None, 98) 6370
dense_4 (Dense) (None, 132) 13068
dense_5 (Dense) (None, 200) 26600
=================================================================
Total params: 91940 (359.14 KB)
Trainable params: 91940 (359.14 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 61: early stopping
latent dim: 64 loss value is: 0.041365187615156174
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 132) 26532
dense_1 (Dense) (None, 98) 13034
dense_2 (Dense) (None, 65) 6435
dense_3 (Dense) (None, 98) 6468
dense_4 (Dense) (None, 132) 13068
dense_5 (Dense) (None, 200) 26600
=================================================================
Total params: 92137 (359.91 KB)
Trainable params: 92137 (359.91 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 55: early stopping
latent dim: 65 loss value is: 0.04522617161273956
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 133) 26733
dense_1 (Dense) (None, 99) 13266
dense_2 (Dense) (None, 66) 6600
dense_3 (Dense) (None, 99) 6633
dense_4 (Dense) (None, 133) 13300
dense_5 (Dense) (None, 200) 26800
=================================================================
Total params: 93332 (364.58 KB)
Trainable params: 93332 (364.58 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 84: early stopping
latent dim: 66 loss value is: 0.04633617401123047
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 133) 26733
dense_1 (Dense) (None, 100) 13400
dense_2 (Dense) (None, 67) 6767
dense_3 (Dense) (None, 100) 6800
dense_4 (Dense) (None, 133) 13433
dense_5 (Dense) (None, 200) 26800
=================================================================
Total params: 93933 (366.93 KB)
Trainable params: 93933 (366.93 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 88: early stopping
latent dim: 67 loss value is: 0.04103975370526314
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 134) 26934
dense_1 (Dense) (None, 101) 13635
dense_2 (Dense) (None, 68) 6936
dense_3 (Dense) (None, 101) 6969
dense_4 (Dense) (None, 134) 13668
dense_5 (Dense) (None, 200) 27000
=================================================================
Total params: 95142 (371.65 KB)
Trainable params: 95142 (371.65 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 82: early stopping
latent dim: 68 loss value is: 0.047556981444358826
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 134) 26934
dense_1 (Dense) (None, 101) 13635
dense_2 (Dense) (None, 69) 7038
dense_3 (Dense) (None, 101) 7070
dense_4 (Dense) (None, 134) 13668
dense_5 (Dense) (None, 200) 27000
=================================================================
Total params: 95345 (372.44 KB)
Trainable params: 95345 (372.44 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 95: early stopping
latent dim: 69 loss value is: 0.03813070058822632
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 135) 27135
dense_1 (Dense) (None, 102) 13872
dense_2 (Dense) (None, 70) 7210
dense_3 (Dense) (None, 102) 7242
dense_4 (Dense) (None, 135) 13905
dense_5 (Dense) (None, 200) 27200
=================================================================
Total params: 96564 (377.20 KB)
Trainable params: 96564 (377.20 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 85: early stopping
latent dim: 70 loss value is: 0.03138085827231407
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 135) 27135
dense_1 (Dense) (None, 103) 14008
dense_2 (Dense) (None, 71) 7384
dense_3 (Dense) (None, 103) 7416
dense_4 (Dense) (None, 135) 14040
dense_5 (Dense) (None, 200) 27200
=================================================================
Total params: 97183 (379.62 KB)
Trainable params: 97183 (379.62 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 87: early stopping
latent dim: 71 loss value is: 0.04561646282672882
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 136) 27336
dense_1 (Dense) (None, 104) 14248
dense_2 (Dense) (None, 72) 7560
dense_3 (Dense) (None, 104) 7592
dense_4 (Dense) (None, 136) 14280
dense_5 (Dense) (None, 200) 27400
=================================================================
Total params: 98416 (384.44 KB)
Trainable params: 98416 (384.44 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 54: early stopping
latent dim: 72 loss value is: 0.044085171073675156
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 136) 27336
dense_1 (Dense) (None, 104) 14248
dense_2 (Dense) (None, 73) 7665
dense_3 (Dense) (None, 104) 7696
dense_4 (Dense) (None, 136) 14280
dense_5 (Dense) (None, 200) 27400
=================================================================
Total params: 98625 (385.25 KB)
Trainable params: 98625 (385.25 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 66: early stopping
latent dim: 73 loss value is: 0.044404324144124985
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 137) 27537
dense_1 (Dense) (None, 105) 14490
dense_2 (Dense) (None, 74) 7844
dense_3 (Dense) (None, 105) 7875
dense_4 (Dense) (None, 137) 14522
dense_5 (Dense) (None, 200) 27600
=================================================================
Total params: 99868 (390.11 KB)
Trainable params: 99868 (390.11 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 78: early stopping
latent dim: 74 loss value is: 0.03714355453848839
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 137) 27537
dense_1 (Dense) (None, 106) 14628
dense_2 (Dense) (None, 75) 8025
dense_3 (Dense) (None, 106) 8056
dense_4 (Dense) (None, 137) 14659
dense_5 (Dense) (None, 200) 27600
=================================================================
Total params: 100505 (392.60 KB)
Trainable params: 100505 (392.60 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 59: early stopping
latent dim: 75 loss value is: 0.03786075487732887
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 138) 27738
dense_1 (Dense) (None, 107) 14873
dense_2 (Dense) (None, 76) 8208
dense_3 (Dense) (None, 107) 8239
dense_4 (Dense) (None, 138) 14904
dense_5 (Dense) (None, 200) 27800
=================================================================
Total params: 101762 (397.51 KB)
Trainable params: 101762 (397.51 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 99: early stopping
latent dim: 76 loss value is: 0.04078849032521248
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 138) 27738
dense_1 (Dense) (None, 107) 14873
dense_2 (Dense) (None, 77) 8316
dense_3 (Dense) (None, 107) 8346
dense_4 (Dense) (None, 138) 14904
dense_5 (Dense) (None, 200) 27800
=================================================================
Total params: 101977 (398.35 KB)
Trainable params: 101977 (398.35 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 97: early stopping
latent dim: 77 loss value is: 0.03816216439008713
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 139) 27939
dense_1 (Dense) (None, 108) 15120
dense_2 (Dense) (None, 78) 8502
dense_3 (Dense) (None, 108) 8532
dense_4 (Dense) (None, 139) 15151
dense_5 (Dense) (None, 200) 28000
=================================================================
Total params: 103244 (403.30 KB)
Trainable params: 103244 (403.30 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 95: early stopping
latent dim: 78 loss value is: 0.03235436603426933
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 139) 27939
dense_1 (Dense) (None, 109) 15260
dense_2 (Dense) (None, 79) 8690
dense_3 (Dense) (None, 109) 8720
dense_4 (Dense) (None, 139) 15290
dense_5 (Dense) (None, 200) 28000
=================================================================
Total params: 103899 (405.86 KB)
Trainable params: 103899 (405.86 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 67: early stopping
latent dim: 79 loss value is: 0.045350685715675354
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 140) 28140
dense_1 (Dense) (None, 110) 15510
dense_2 (Dense) (None, 80) 8880
dense_3 (Dense) (None, 110) 8910
dense_4 (Dense) (None, 140) 15540
dense_5 (Dense) (None, 200) 28200
=================================================================
Total params: 105180 (410.86 KB)
Trainable params: 105180 (410.86 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 124: early stopping
latent dim: 80 loss value is: 0.04018225148320198
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 140) 28140
dense_1 (Dense) (None, 110) 15510
dense_2 (Dense) (None, 81) 8991
dense_3 (Dense) (None, 110) 9020
dense_4 (Dense) (None, 140) 15540
dense_5 (Dense) (None, 200) 28200
=================================================================
Total params: 105401 (411.72 KB)
Trainable params: 105401 (411.72 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 103: early stopping
latent dim: 81 loss value is: 0.03301086276769638
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 141) 28341
dense_1 (Dense) (None, 111) 15762
dense_2 (Dense) (None, 82) 9184
dense_3 (Dense) (None, 111) 9213
dense_4 (Dense) (None, 141) 15792
dense_5 (Dense) (None, 200) 28400
=================================================================
Total params: 106692 (416.77 KB)
Trainable params: 106692 (416.77 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 65: early stopping
latent dim: 82 loss value is: 0.036501020193099976
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 141) 28341
dense_1 (Dense) (None, 112) 15904
dense_2 (Dense) (None, 83) 9379
dense_3 (Dense) (None, 112) 9408
dense_4 (Dense) (None, 141) 15933
dense_5 (Dense) (None, 200) 28400
=================================================================
Total params: 107365 (419.39 KB)
Trainable params: 107365 (419.39 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 100: early stopping
latent dim: 83 loss value is: 0.04048740118741989
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 142) 28542
dense_1 (Dense) (None, 113) 16159
dense_2 (Dense) (None, 84) 9576
dense_3 (Dense) (None, 113) 9605
dense_4 (Dense) (None, 142) 16188
dense_5 (Dense) (None, 200) 28600
=================================================================
Total params: 108670 (424.49 KB)
Trainable params: 108670 (424.49 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 68: early stopping
latent dim: 84 loss value is: 0.051125120371580124
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 142) 28542
dense_1 (Dense) (None, 113) 16159
dense_2 (Dense) (None, 85) 9690
dense_3 (Dense) (None, 113) 9718
dense_4 (Dense) (None, 142) 16188
dense_5 (Dense) (None, 200) 28600
=================================================================
Total params: 108897 (425.38 KB)
Trainable params: 108897 (425.38 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 76: early stopping
latent dim: 85 loss value is: 0.045421261340379715
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 143) 28743
dense_1 (Dense) (None, 114) 16416
dense_2 (Dense) (None, 86) 9890
dense_3 (Dense) (None, 114) 9918
dense_4 (Dense) (None, 143) 16445
dense_5 (Dense) (None, 200) 28800
=================================================================
Total params: 110212 (430.52 KB)
Trainable params: 110212 (430.52 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 70: early stopping
latent dim: 86 loss value is: 0.04232103377580643
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 143) 28743
dense_1 (Dense) (None, 115) 16560
dense_2 (Dense) (None, 87) 10092
dense_3 (Dense) (None, 115) 10120
dense_4 (Dense) (None, 143) 16588
dense_5 (Dense) (None, 200) 28800
=================================================================
Total params: 110903 (433.21 KB)
Trainable params: 110903 (433.21 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 96: early stopping
latent dim: 87 loss value is: 0.038700249046087265
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 144) 28944
dense_1 (Dense) (None, 116) 16820
dense_2 (Dense) (None, 88) 10296
dense_3 (Dense) (None, 116) 10324
dense_4 (Dense) (None, 144) 16848
dense_5 (Dense) (None, 200) 29000
=================================================================
Total params: 112232 (438.41 KB)
Trainable params: 112232 (438.41 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 64: early stopping
latent dim: 88 loss value is: 0.03938958793878555
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 144) 28944
dense_1 (Dense) (None, 116) 16820
dense_2 (Dense) (None, 89) 10413
dense_3 (Dense) (None, 116) 10440
dense_4 (Dense) (None, 144) 16848
dense_5 (Dense) (None, 200) 29000
=================================================================
Total params: 112465 (439.32 KB)
Trainable params: 112465 (439.32 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 49: early stopping
latent dim: 89 loss value is: 0.04708300903439522
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 145) 29145
dense_1 (Dense) (None, 117) 17082
dense_2 (Dense) (None, 90) 10620
dense_3 (Dense) (None, 117) 10647
dense_4 (Dense) (None, 145) 17110
dense_5 (Dense) (None, 200) 29200
=================================================================
Total params: 113804 (444.55 KB)
Trainable params: 113804 (444.55 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 55: early stopping
latent dim: 90 loss value is: 0.038739293813705444
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 145) 29145
dense_1 (Dense) (None, 118) 17228
dense_2 (Dense) (None, 91) 10829
dense_3 (Dense) (None, 118) 10856
dense_4 (Dense) (None, 145) 17255
dense_5 (Dense) (None, 200) 29200
=================================================================
Total params: 114513 (447.32 KB)
Trainable params: 114513 (447.32 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 82: early stopping
latent dim: 91 loss value is: 0.044935114681720734
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 146) 29346
dense_1 (Dense) (None, 119) 17493
dense_2 (Dense) (None, 92) 11040
dense_3 (Dense) (None, 119) 11067
dense_4 (Dense) (None, 146) 17520
dense_5 (Dense) (None, 200) 29400
=================================================================
Total params: 115866 (452.60 KB)
Trainable params: 115866 (452.60 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 51: early stopping
latent dim: 92 loss value is: 0.04488666355609894
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 146) 29346
dense_1 (Dense) (None, 119) 17493
dense_2 (Dense) (None, 93) 11160
dense_3 (Dense) (None, 119) 11186
dense_4 (Dense) (None, 146) 17520
dense_5 (Dense) (None, 200) 29400
=================================================================
Total params: 116105 (453.54 KB)
Trainable params: 116105 (453.54 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 47: early stopping
latent dim: 93 loss value is: 0.042802341282367706
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 147) 29547
dense_1 (Dense) (None, 120) 17760
dense_2 (Dense) (None, 94) 11374
dense_3 (Dense) (None, 120) 11400
dense_4 (Dense) (None, 147) 17787
dense_5 (Dense) (None, 200) 29600
=================================================================
Total params: 117468 (458.86 KB)
Trainable params: 117468 (458.86 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 71: early stopping
latent dim: 94 loss value is: 0.0432349368929863
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 147) 29547
dense_1 (Dense) (None, 121) 17908
dense_2 (Dense) (None, 95) 11590
dense_3 (Dense) (None, 121) 11616
dense_4 (Dense) (None, 147) 17934
dense_5 (Dense) (None, 200) 29600
=================================================================
Total params: 118195 (461.70 KB)
Trainable params: 118195 (461.70 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 57: early stopping
latent dim: 95 loss value is: 0.04410687834024429
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 148) 29748
dense_1 (Dense) (None, 122) 18178
dense_2 (Dense) (None, 96) 11808
dense_3 (Dense) (None, 122) 11834
dense_4 (Dense) (None, 148) 18204
dense_5 (Dense) (None, 200) 29800
=================================================================
Total params: 119572 (467.08 KB)
Trainable params: 119572 (467.08 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 92: early stopping
latent dim: 96 loss value is: 0.03631843626499176
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 148) 29748
dense_1 (Dense) (None, 122) 18178
dense_2 (Dense) (None, 97) 11931
dense_3 (Dense) (None, 122) 11956
dense_4 (Dense) (None, 148) 18204
dense_5 (Dense) (None, 200) 29800
=================================================================
Total params: 119817 (468.04 KB)
Trainable params: 119817 (468.04 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 104: early stopping
latent dim: 97 loss value is: 0.04838600754737854
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 149) 29949
dense_1 (Dense) (None, 123) 18450
dense_2 (Dense) (None, 98) 12152
dense_3 (Dense) (None, 123) 12177
dense_4 (Dense) (None, 149) 18476
dense_5 (Dense) (None, 200) 30000
=================================================================
Total params: 121204 (473.45 KB)
Trainable params: 121204 (473.45 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 81: early stopping
latent dim: 98 loss value is: 0.04569413885474205
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 149) 29949
dense_1 (Dense) (None, 124) 18600
dense_2 (Dense) (None, 99) 12375
dense_3 (Dense) (None, 124) 12400
dense_4 (Dense) (None, 149) 18625
dense_5 (Dense) (None, 200) 30000
=================================================================
Total params: 121949 (476.36 KB)
Trainable params: 121949 (476.36 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 61: early stopping
latent dim: 99 loss value is: 0.041785795241594315
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 150) 30150
dense_1 (Dense) (None, 125) 18875
dense_2 (Dense) (None, 100) 12600
dense_3 (Dense) (None, 125) 12625
dense_4 (Dense) (None, 150) 18900
dense_5 (Dense) (None, 200) 30200
=================================================================
Total params: 123350 (481.84 KB)
Trainable params: 123350 (481.84 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 84: early stopping
latent dim: 100 loss value is: 0.041492629796266556
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 150) 30150
dense_1 (Dense) (None, 125) 18875
dense_2 (Dense) (None, 101) 12726
dense_3 (Dense) (None, 125) 12750
dense_4 (Dense) (None, 150) 18900
dense_5 (Dense) (None, 200) 30200
=================================================================
Total params: 123601 (482.82 KB)
Trainable params: 123601 (482.82 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 64: early stopping
latent dim: 101 loss value is: 0.04314511641860008
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 151) 30351
dense_1 (Dense) (None, 126) 19152
dense_2 (Dense) (None, 102) 12954
dense_3 (Dense) (None, 126) 12978
dense_4 (Dense) (None, 151) 19177
dense_5 (Dense) (None, 200) 30400
=================================================================
Total params: 125012 (488.33 KB)
Trainable params: 125012 (488.33 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 68: early stopping
latent dim: 102 loss value is: 0.04628290608525276
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 151) 30351
dense_1 (Dense) (None, 127) 19304
dense_2 (Dense) (None, 103) 13184
dense_3 (Dense) (None, 127) 13208
dense_4 (Dense) (None, 151) 19328
dense_5 (Dense) (None, 200) 30400
=================================================================
Total params: 125775 (491.31 KB)
Trainable params: 125775 (491.31 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 87: early stopping
latent dim: 103 loss value is: 0.04614529386162758
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 152) 30552
dense_1 (Dense) (None, 128) 19584
dense_2 (Dense) (None, 104) 13416
dense_3 (Dense) (None, 128) 13440
dense_4 (Dense) (None, 152) 19608
dense_5 (Dense) (None, 200) 30600
=================================================================
Total params: 127200 (496.88 KB)
Trainable params: 127200 (496.88 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 110: early stopping
latent dim: 104 loss value is: 0.04238561913371086
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 152) 30552
dense_1 (Dense) (None, 128) 19584
dense_2 (Dense) (None, 105) 13545
dense_3 (Dense) (None, 128) 13568
dense_4 (Dense) (None, 152) 19608
dense_5 (Dense) (None, 200) 30600
=================================================================
Total params: 127457 (497.88 KB)
Trainable params: 127457 (497.88 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 53: early stopping
latent dim: 105 loss value is: 0.04664560407400131
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 153) 30753
dense_1 (Dense) (None, 129) 19866
dense_2 (Dense) (None, 106) 13780
dense_3 (Dense) (None, 129) 13803
dense_4 (Dense) (None, 153) 19890
dense_5 (Dense) (None, 200) 30800
=================================================================
Total params: 128892 (503.48 KB)
Trainable params: 128892 (503.48 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 52: early stopping
latent dim: 106 loss value is: 0.04498232528567314
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 153) 30753
dense_1 (Dense) (None, 130) 20020
dense_2 (Dense) (None, 107) 14017
dense_3 (Dense) (None, 130) 14040
dense_4 (Dense) (None, 153) 20043
dense_5 (Dense) (None, 200) 30800
=================================================================
Total params: 129673 (506.54 KB)
Trainable params: 129673 (506.54 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 110: early stopping
latent dim: 107 loss value is: 0.03638826310634613
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 154) 30954
dense_1 (Dense) (None, 131) 20305
dense_2 (Dense) (None, 108) 14256
dense_3 (Dense) (None, 131) 14279
dense_4 (Dense) (None, 154) 20328
dense_5 (Dense) (None, 200) 31000
=================================================================
Total params: 131122 (512.20 KB)
Trainable params: 131122 (512.20 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 94: early stopping
latent dim: 108 loss value is: 0.0421459935605526
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 154) 30954
dense_1 (Dense) (None, 131) 20305
dense_2 (Dense) (None, 109) 14388
dense_3 (Dense) (None, 131) 14410
dense_4 (Dense) (None, 154) 20328
dense_5 (Dense) (None, 200) 31000
=================================================================
Total params: 131385 (513.22 KB)
Trainable params: 131385 (513.22 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 78: early stopping
latent dim: 109 loss value is: 0.04409986734390259
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 155) 31155
dense_1 (Dense) (None, 132) 20592
dense_2 (Dense) (None, 110) 14630
dense_3 (Dense) (None, 132) 14652
dense_4 (Dense) (None, 155) 20615
dense_5 (Dense) (None, 200) 31200
=================================================================
Total params: 132844 (518.92 KB)
Trainable params: 132844 (518.92 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 55: early stopping
latent dim: 110 loss value is: 0.04961726814508438
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 155) 31155
dense_1 (Dense) (None, 133) 20748
dense_2 (Dense) (None, 111) 14874
dense_3 (Dense) (None, 133) 14896
dense_4 (Dense) (None, 155) 20770
dense_5 (Dense) (None, 200) 31200
=================================================================
Total params: 133643 (522.04 KB)
Trainable params: 133643 (522.04 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 84: early stopping
latent dim: 111 loss value is: 0.050564978271722794
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 156) 31356
dense_1 (Dense) (None, 134) 21038
dense_2 (Dense) (None, 112) 15120
dense_3 (Dense) (None, 134) 15142
dense_4 (Dense) (None, 156) 21060
dense_5 (Dense) (None, 200) 31400
=================================================================
Total params: 135116 (527.80 KB)
Trainable params: 135116 (527.80 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 85: early stopping
latent dim: 112 loss value is: 0.04674302414059639
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 156) 31356
dense_1 (Dense) (None, 134) 21038
dense_2 (Dense) (None, 113) 15255
dense_3 (Dense) (None, 134) 15276
dense_4 (Dense) (None, 156) 21060
dense_5 (Dense) (None, 200) 31400
=================================================================
Total params: 135385 (528.85 KB)
Trainable params: 135385 (528.85 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 119: early stopping
latent dim: 113 loss value is: 0.04260950908064842
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 157) 31557
dense_1 (Dense) (None, 135) 21330
dense_2 (Dense) (None, 114) 15504
dense_3 (Dense) (None, 135) 15525
dense_4 (Dense) (None, 157) 21352
dense_5 (Dense) (None, 200) 31600
=================================================================
Total params: 136868 (534.64 KB)
Trainable params: 136868 (534.64 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 74: early stopping
latent dim: 114 loss value is: 0.04744070768356323
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 157) 31557
dense_1 (Dense) (None, 136) 21488
dense_2 (Dense) (None, 115) 15755
dense_3 (Dense) (None, 136) 15776
dense_4 (Dense) (None, 157) 21509
dense_5 (Dense) (None, 200) 31600
=================================================================
Total params: 137685 (537.83 KB)
Trainable params: 137685 (537.83 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 58: early stopping
latent dim: 115 loss value is: 0.04961918666958809
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 158) 31758
dense_1 (Dense) (None, 137) 21783
dense_2 (Dense) (None, 116) 16008
dense_3 (Dense) (None, 137) 16029
dense_4 (Dense) (None, 158) 21804
dense_5 (Dense) (None, 200) 31800
=================================================================
Total params: 139182 (543.68 KB)
Trainable params: 139182 (543.68 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 57: early stopping
latent dim: 116 loss value is: 0.0474635474383831
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 158) 31758
dense_1 (Dense) (None, 137) 21783
dense_2 (Dense) (None, 117) 16146
dense_3 (Dense) (None, 137) 16166
dense_4 (Dense) (None, 158) 21804
dense_5 (Dense) (None, 200) 31800
=================================================================
Total params: 139457 (544.75 KB)
Trainable params: 139457 (544.75 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 53: early stopping
latent dim: 117 loss value is: 0.0407366119325161
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 159) 31959
dense_1 (Dense) (None, 138) 22080
dense_2 (Dense) (None, 118) 16402
dense_3 (Dense) (None, 138) 16422
dense_4 (Dense) (None, 159) 22101
dense_5 (Dense) (None, 200) 32000
=================================================================
Total params: 140964 (550.64 KB)
Trainable params: 140964 (550.64 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 60: early stopping
latent dim: 118 loss value is: 0.050539400428533554
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 159) 31959
dense_1 (Dense) (None, 139) 22240
dense_2 (Dense) (None, 119) 16660
dense_3 (Dense) (None, 139) 16680
dense_4 (Dense) (None, 159) 22260
dense_5 (Dense) (None, 200) 32000
=================================================================
Total params: 141799 (553.90 KB)
Trainable params: 141799 (553.90 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 111: early stopping
latent dim: 119 loss value is: 0.04068679362535477
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 160) 32160
dense_1 (Dense) (None, 140) 22540
dense_2 (Dense) (None, 120) 16920
dense_3 (Dense) (None, 140) 16940
dense_4 (Dense) (None, 160) 22560
dense_5 (Dense) (None, 200) 32200
=================================================================
Total params: 143320 (559.84 KB)
Trainable params: 143320 (559.84 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 49: early stopping
latent dim: 120 loss value is: 0.04429227113723755
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 160) 32160
dense_1 (Dense) (None, 140) 22540
dense_2 (Dense) (None, 121) 17061
dense_3 (Dense) (None, 140) 17080
dense_4 (Dense) (None, 160) 22560
dense_5 (Dense) (None, 200) 32200
=================================================================
Total params: 143601 (560.94 KB)
Trainable params: 143601 (560.94 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 59: early stopping
latent dim: 121 loss value is: 0.034989550709724426
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 161) 32361
dense_1 (Dense) (None, 141) 22842
dense_2 (Dense) (None, 122) 17324
dense_3 (Dense) (None, 141) 17343
dense_4 (Dense) (None, 161) 22862
dense_5 (Dense) (None, 200) 32400
=================================================================
Total params: 145132 (566.92 KB)
Trainable params: 145132 (566.92 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 79: early stopping
latent dim: 122 loss value is: 0.04515182226896286
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 161) 32361
dense_1 (Dense) (None, 142) 23004
dense_2 (Dense) (None, 123) 17589
dense_3 (Dense) (None, 142) 17608
dense_4 (Dense) (None, 161) 23023
dense_5 (Dense) (None, 200) 32400
=================================================================
Total params: 145985 (570.25 KB)
Trainable params: 145985 (570.25 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 89: early stopping
latent dim: 123 loss value is: 0.04167165607213974
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 162) 32562
dense_1 (Dense) (None, 143) 23309
dense_2 (Dense) (None, 124) 17856
dense_3 (Dense) (None, 143) 17875
dense_4 (Dense) (None, 162) 23328
dense_5 (Dense) (None, 200) 32600
=================================================================
Total params: 147530 (576.29 KB)
Trainable params: 147530 (576.29 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 75: early stopping
latent dim: 124 loss value is: 0.040396884083747864
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 162) 32562
dense_1 (Dense) (None, 143) 23309
dense_2 (Dense) (None, 125) 18000
dense_3 (Dense) (None, 143) 18018
dense_4 (Dense) (None, 162) 23328
dense_5 (Dense) (None, 200) 32600
=================================================================
Total params: 147817 (577.41 KB)
Trainable params: 147817 (577.41 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 95: early stopping
latent dim: 125 loss value is: 0.043646931648254395
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 163) 32763
dense_1 (Dense) (None, 144) 23616
dense_2 (Dense) (None, 126) 18270
dense_3 (Dense) (None, 144) 18288
dense_4 (Dense) (None, 163) 23635
dense_5 (Dense) (None, 200) 32800
=================================================================
Total params: 149372 (583.48 KB)
Trainable params: 149372 (583.48 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 50: early stopping
latent dim: 126 loss value is: 0.04107265546917915
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 163) 32763
dense_1 (Dense) (None, 145) 23780
dense_2 (Dense) (None, 127) 18542
dense_3 (Dense) (None, 145) 18560
dense_4 (Dense) (None, 163) 23798
dense_5 (Dense) (None, 200) 32800
=================================================================
Total params: 150243 (586.89 KB)
Trainable params: 150243 (586.89 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 89: early stopping
latent dim: 127 loss value is: 0.046293798834085464
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 164) 32964
dense_1 (Dense) (None, 146) 24090
dense_2 (Dense) (None, 128) 18816
dense_3 (Dense) (None, 146) 18834
dense_4 (Dense) (None, 164) 24108
dense_5 (Dense) (None, 200) 33000
=================================================================
Total params: 151812 (593.02 KB)
Trainable params: 151812 (593.02 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 76: early stopping
latent dim: 128 loss value is: 0.03986804187297821
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 164) 32964
dense_1 (Dense) (None, 146) 24090
dense_2 (Dense) (None, 129) 18963
dense_3 (Dense) (None, 146) 18980
dense_4 (Dense) (None, 164) 24108
dense_5 (Dense) (None, 200) 33000
=================================================================
Total params: 152105 (594.16 KB)
Trainable params: 152105 (594.16 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 59: early stopping
latent dim: 129 loss value is: 0.03923327103257179
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 165) 33165
dense_1 (Dense) (None, 147) 24402
dense_2 (Dense) (None, 130) 19240
dense_3 (Dense) (None, 147) 19257
dense_4 (Dense) (None, 165) 24420
dense_5 (Dense) (None, 200) 33200
=================================================================
Total params: 153684 (600.33 KB)
Trainable params: 153684 (600.33 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 50: early stopping
latent dim: 130 loss value is: 0.04506026953458786
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 165) 33165
dense_1 (Dense) (None, 148) 24568
dense_2 (Dense) (None, 131) 19519
dense_3 (Dense) (None, 148) 19536
dense_4 (Dense) (None, 165) 24585
dense_5 (Dense) (None, 200) 33200
=================================================================
Total params: 154573 (603.80 KB)
Trainable params: 154573 (603.80 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 95: early stopping
latent dim: 131 loss value is: 0.04300656169652939
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 166) 33366
dense_1 (Dense) (None, 149) 24883
dense_2 (Dense) (None, 132) 19800
dense_3 (Dense) (None, 149) 19817
dense_4 (Dense) (None, 166) 24900
dense_5 (Dense) (None, 200) 33400
=================================================================
Total params: 156166 (610.02 KB)
Trainable params: 156166 (610.02 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 43: early stopping
latent dim: 132 loss value is: 0.04969264194369316
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 166) 33366
dense_1 (Dense) (None, 149) 24883
dense_2 (Dense) (None, 133) 19950
dense_3 (Dense) (None, 149) 19966
dense_4 (Dense) (None, 166) 24900
dense_5 (Dense) (None, 200) 33400
=================================================================
Total params: 156465 (611.19 KB)
Trainable params: 156465 (611.19 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 51: early stopping
latent dim: 133 loss value is: 0.046885278075933456
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 167) 33567
dense_1 (Dense) (None, 150) 25200
dense_2 (Dense) (None, 134) 20234
dense_3 (Dense) (None, 150) 20250
dense_4 (Dense) (None, 167) 25217
dense_5 (Dense) (None, 200) 33600
=================================================================
Total params: 158068 (617.45 KB)
Trainable params: 158068 (617.45 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 46: early stopping
latent dim: 134 loss value is: 0.045247625559568405
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 167) 33567
dense_1 (Dense) (None, 151) 25368
dense_2 (Dense) (None, 135) 20520
dense_3 (Dense) (None, 151) 20536
dense_4 (Dense) (None, 167) 25384
dense_5 (Dense) (None, 200) 33600
=================================================================
Total params: 158975 (621.00 KB)
Trainable params: 158975 (621.00 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 44: early stopping
latent dim: 135 loss value is: 0.045315079391002655
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 168) 33768
dense_1 (Dense) (None, 152) 25688
dense_2 (Dense) (None, 136) 20808
dense_3 (Dense) (None, 152) 20824
dense_4 (Dense) (None, 168) 25704
dense_5 (Dense) (None, 200) 33800
=================================================================
Total params: 160592 (627.31 KB)
Trainable params: 160592 (627.31 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 48: early stopping
latent dim: 136 loss value is: 0.0485621877014637
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 168) 33768
dense_1 (Dense) (None, 152) 25688
dense_2 (Dense) (None, 137) 20961
dense_3 (Dense) (None, 152) 20976
dense_4 (Dense) (None, 168) 25704
dense_5 (Dense) (None, 200) 33800
=================================================================
Total params: 160897 (628.50 KB)
Trainable params: 160897 (628.50 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 84: early stopping
latent dim: 137 loss value is: 0.04513256996870041
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 169) 33969
dense_1 (Dense) (None, 153) 26010
dense_2 (Dense) (None, 138) 21252
dense_3 (Dense) (None, 153) 21267
dense_4 (Dense) (None, 169) 26026
dense_5 (Dense) (None, 200) 34000
=================================================================
Total params: 162524 (634.86 KB)
Trainable params: 162524 (634.86 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 81: early stopping
latent dim: 138 loss value is: 0.05356280505657196
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 169) 33969
dense_1 (Dense) (None, 154) 26180
dense_2 (Dense) (None, 139) 21545
dense_3 (Dense) (None, 154) 21560
dense_4 (Dense) (None, 169) 26195
dense_5 (Dense) (None, 200) 34000
=================================================================
Total params: 163449 (638.47 KB)
Trainable params: 163449 (638.47 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 74: early stopping
latent dim: 139 loss value is: 0.041922129690647125
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 170) 34170
dense_1 (Dense) (None, 155) 26505
dense_2 (Dense) (None, 140) 21840
dense_3 (Dense) (None, 155) 21855
dense_4 (Dense) (None, 170) 26520
dense_5 (Dense) (None, 200) 34200
=================================================================
Total params: 165090 (644.88 KB)
Trainable params: 165090 (644.88 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 45: early stopping
latent dim: 140 loss value is: 0.03985287621617317
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 170) 34170
dense_1 (Dense) (None, 155) 26505
dense_2 (Dense) (None, 141) 21996
dense_3 (Dense) (None, 155) 22010
dense_4 (Dense) (None, 170) 26520
dense_5 (Dense) (None, 200) 34200
=================================================================
Total params: 165401 (646.10 KB)
Trainable params: 165401 (646.10 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 67: early stopping
latent dim: 141 loss value is: 0.051768820732831955
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 171) 34371
dense_1 (Dense) (None, 156) 26832
dense_2 (Dense) (None, 142) 22294
dense_3 (Dense) (None, 156) 22308
dense_4 (Dense) (None, 171) 26847
dense_5 (Dense) (None, 200) 34400
=================================================================
Total params: 167052 (652.55 KB)
Trainable params: 167052 (652.55 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 71: early stopping
latent dim: 142 loss value is: 0.04466984048485756
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 171) 34371
dense_1 (Dense) (None, 157) 27004
dense_2 (Dense) (None, 143) 22594
dense_3 (Dense) (None, 157) 22608
dense_4 (Dense) (None, 171) 27018
dense_5 (Dense) (None, 200) 34400
=================================================================
Total params: 167995 (656.23 KB)
Trainable params: 167995 (656.23 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 47: early stopping
latent dim: 143 loss value is: 0.04644864797592163
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 172) 34572
dense_1 (Dense) (None, 158) 27334
dense_2 (Dense) (None, 144) 22896
dense_3 (Dense) (None, 158) 22910
dense_4 (Dense) (None, 172) 27348
dense_5 (Dense) (None, 200) 34600
=================================================================
Total params: 169660 (662.73 KB)
Trainable params: 169660 (662.73 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 45: early stopping
latent dim: 144 loss value is: 0.04423432797193527
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 172) 34572
dense_1 (Dense) (None, 158) 27334
dense_2 (Dense) (None, 145) 23055
dense_3 (Dense) (None, 158) 23068
dense_4 (Dense) (None, 172) 27348
dense_5 (Dense) (None, 200) 34600
=================================================================
Total params: 169977 (663.97 KB)
Trainable params: 169977 (663.97 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 48: early stopping
latent dim: 145 loss value is: 0.04254532232880592
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 173) 34773
dense_1 (Dense) (None, 159) 27666
dense_2 (Dense) (None, 146) 23360
dense_3 (Dense) (None, 159) 23373
dense_4 (Dense) (None, 173) 27680
dense_5 (Dense) (None, 200) 34800
=================================================================
Total params: 171652 (670.52 KB)
Trainable params: 171652 (670.52 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 45: early stopping
latent dim: 146 loss value is: 0.04470058158040047
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 173) 34773
dense_1 (Dense) (None, 160) 27840
dense_2 (Dense) (None, 147) 23667
dense_3 (Dense) (None, 160) 23680
dense_4 (Dense) (None, 173) 27853
dense_5 (Dense) (None, 200) 34800
=================================================================
Total params: 172613 (674.27 KB)
Trainable params: 172613 (674.27 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 50: early stopping
latent dim: 147 loss value is: 0.04581195116043091
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 174) 34974
dense_1 (Dense) (None, 161) 28175
dense_2 (Dense) (None, 148) 23976
dense_3 (Dense) (None, 161) 23989
dense_4 (Dense) (None, 174) 28188
dense_5 (Dense) (None, 200) 35000
=================================================================
Total params: 174302 (680.87 KB)
Trainable params: 174302 (680.87 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 106: early stopping
latent dim: 148 loss value is: 0.051705121994018555
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 174) 34974
dense_1 (Dense) (None, 161) 28175
dense_2 (Dense) (None, 149) 24138
dense_3 (Dense) (None, 161) 24150
dense_4 (Dense) (None, 174) 28188
dense_5 (Dense) (None, 200) 35000
=================================================================
Total params: 174625 (682.13 KB)
Trainable params: 174625 (682.13 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 45: early stopping
latent dim: 149 loss value is: 0.034191302955150604
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 175) 35175
dense_1 (Dense) (None, 162) 28512
dense_2 (Dense) (None, 150) 24450
dense_3 (Dense) (None, 162) 24462
dense_4 (Dense) (None, 175) 28525
dense_5 (Dense) (None, 200) 35200
=================================================================
Total params: 176324 (688.77 KB)
Trainable params: 176324 (688.77 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 73: early stopping
latent dim: 150 loss value is: 0.041316043585538864
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 175) 35175
dense_1 (Dense) (None, 163) 28688
dense_2 (Dense) (None, 151) 24764
dense_3 (Dense) (None, 163) 24776
dense_4 (Dense) (None, 175) 28700
dense_5 (Dense) (None, 200) 35200
=================================================================
Total params: 177303 (692.59 KB)
Trainable params: 177303 (692.59 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 57: early stopping
latent dim: 151 loss value is: 0.04009689390659332
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 176) 35376
dense_1 (Dense) (None, 164) 29028
dense_2 (Dense) (None, 152) 25080
dense_3 (Dense) (None, 164) 25092
dense_4 (Dense) (None, 176) 29040
dense_5 (Dense) (None, 200) 35400
=================================================================
Total params: 179016 (699.28 KB)
Trainable params: 179016 (699.28 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 43: early stopping
latent dim: 152 loss value is: 0.054968394339084625
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 176) 35376
dense_1 (Dense) (None, 164) 29028
dense_2 (Dense) (None, 153) 25245
dense_3 (Dense) (None, 164) 25256
dense_4 (Dense) (None, 176) 29040
dense_5 (Dense) (None, 200) 35400
=================================================================
Total params: 179345 (700.57 KB)
Trainable params: 179345 (700.57 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 62: early stopping
latent dim: 153 loss value is: 0.04161085560917854
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 177) 35577
dense_1 (Dense) (None, 165) 29370
dense_2 (Dense) (None, 154) 25564
dense_3 (Dense) (None, 165) 25575
dense_4 (Dense) (None, 177) 29382
dense_5 (Dense) (None, 200) 35600
=================================================================
Total params: 181068 (707.30 KB)
Trainable params: 181068 (707.30 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 65: early stopping
latent dim: 154 loss value is: 0.04754334315657616
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 177) 35577
dense_1 (Dense) (None, 166) 29548
dense_2 (Dense) (None, 155) 25885
dense_3 (Dense) (None, 166) 25896
dense_4 (Dense) (None, 177) 29559
dense_5 (Dense) (None, 200) 35600
=================================================================
Total params: 182065 (711.19 KB)
Trainable params: 182065 (711.19 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 64: early stopping
latent dim: 155 loss value is: 0.036705974489450455
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 178) 35778
dense_1 (Dense) (None, 167) 29893
dense_2 (Dense) (None, 156) 26208
dense_3 (Dense) (None, 167) 26219
dense_4 (Dense) (None, 178) 29904
dense_5 (Dense) (None, 200) 35800
=================================================================
Total params: 183802 (717.98 KB)
Trainable params: 183802 (717.98 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 90: early stopping
latent dim: 156 loss value is: 0.04242768511176109
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 178) 35778
dense_1 (Dense) (None, 167) 29893
dense_2 (Dense) (None, 157) 26376
dense_3 (Dense) (None, 167) 26386
dense_4 (Dense) (None, 178) 29904
dense_5 (Dense) (None, 200) 35800
=================================================================
Total params: 184137 (719.29 KB)
Trainable params: 184137 (719.29 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 75: early stopping
latent dim: 157 loss value is: 0.047599487006664276
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 179) 35979
dense_1 (Dense) (None, 168) 30240
dense_2 (Dense) (None, 158) 26702
dense_3 (Dense) (None, 168) 26712
dense_4 (Dense) (None, 179) 30251
dense_5 (Dense) (None, 200) 36000
=================================================================
Total params: 185884 (726.11 KB)
Trainable params: 185884 (726.11 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 58: early stopping
latent dim: 158 loss value is: 0.04062032327055931
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 179) 35979
dense_1 (Dense) (None, 169) 30420
dense_2 (Dense) (None, 159) 27030
dense_3 (Dense) (None, 169) 27040
dense_4 (Dense) (None, 179) 30430
dense_5 (Dense) (None, 200) 36000
=================================================================
Total params: 186899 (730.07 KB)
Trainable params: 186899 (730.07 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 57: early stopping
latent dim: 159 loss value is: 0.04136406257748604
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 180) 36180
dense_1 (Dense) (None, 170) 30770
dense_2 (Dense) (None, 160) 27360
dense_3 (Dense) (None, 170) 27370
dense_4 (Dense) (None, 180) 30780
dense_5 (Dense) (None, 200) 36200
=================================================================
Total params: 188660 (736.95 KB)
Trainable params: 188660 (736.95 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 44: early stopping
latent dim: 160 loss value is: 0.05585438758134842
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 180) 36180
dense_1 (Dense) (None, 170) 30770
dense_2 (Dense) (None, 161) 27531
dense_3 (Dense) (None, 170) 27540
dense_4 (Dense) (None, 180) 30780
dense_5 (Dense) (None, 200) 36200
=================================================================
Total params: 189001 (738.29 KB)
Trainable params: 189001 (738.29 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 57: early stopping
latent dim: 161 loss value is: 0.049320247024297714
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 181) 36381
dense_1 (Dense) (None, 171) 31122
dense_2 (Dense) (None, 162) 27864
dense_3 (Dense) (None, 171) 27873
dense_4 (Dense) (None, 181) 31132
dense_5 (Dense) (None, 200) 36400
=================================================================
Total params: 190772 (745.20 KB)
Trainable params: 190772 (745.20 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 53: early stopping
latent dim: 162 loss value is: 0.05213191360235214
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 181) 36381
dense_1 (Dense) (None, 172) 31304
dense_2 (Dense) (None, 163) 28199
dense_3 (Dense) (None, 172) 28208
dense_4 (Dense) (None, 181) 31313
dense_5 (Dense) (None, 200) 36400
=================================================================
Total params: 191805 (749.24 KB)
Trainable params: 191805 (749.24 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 43: early stopping
latent dim: 163 loss value is: 0.045041054487228394
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 182) 36582
dense_1 (Dense) (None, 173) 31659
dense_2 (Dense) (None, 164) 28536
dense_3 (Dense) (None, 173) 28545
dense_4 (Dense) (None, 182) 31668
dense_5 (Dense) (None, 200) 36600
=================================================================
Total params: 193590 (756.21 KB)
Trainable params: 193590 (756.21 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 52: early stopping
latent dim: 164 loss value is: 0.04923431947827339
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 182) 36582
dense_1 (Dense) (None, 173) 31659
dense_2 (Dense) (None, 165) 28710
dense_3 (Dense) (None, 173) 28718
dense_4 (Dense) (None, 182) 31668
dense_5 (Dense) (None, 200) 36600
=================================================================
Total params: 193937 (757.57 KB)
Trainable params: 193937 (757.57 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 46: early stopping
latent dim: 165 loss value is: 0.04163200035691261
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 183) 36783
dense_1 (Dense) (None, 174) 32016
dense_2 (Dense) (None, 166) 29050
dense_3 (Dense) (None, 174) 29058
dense_4 (Dense) (None, 183) 32025
dense_5 (Dense) (None, 200) 36800
=================================================================
Total params: 195732 (764.58 KB)
Trainable params: 195732 (764.58 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 47: early stopping
latent dim: 166 loss value is: 0.03906145691871643
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 183) 36783
dense_1 (Dense) (None, 175) 32200
dense_2 (Dense) (None, 167) 29392
dense_3 (Dense) (None, 175) 29400
dense_4 (Dense) (None, 183) 32208
dense_5 (Dense) (None, 200) 36800
=================================================================
Total params: 196783 (768.68 KB)
Trainable params: 196783 (768.68 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 55: early stopping
latent dim: 167 loss value is: 0.04632195085287094
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 184) 36984
dense_1 (Dense) (None, 176) 32560
dense_2 (Dense) (None, 168) 29736
dense_3 (Dense) (None, 176) 29744
dense_4 (Dense) (None, 184) 32568
dense_5 (Dense) (None, 200) 37000
=================================================================
Total params: 198592 (775.75 KB)
Trainable params: 198592 (775.75 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 51: early stopping
latent dim: 168 loss value is: 0.04824569821357727
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 184) 36984
dense_1 (Dense) (None, 176) 32560
dense_2 (Dense) (None, 169) 29913
dense_3 (Dense) (None, 176) 29920
dense_4 (Dense) (None, 184) 32568
dense_5 (Dense) (None, 200) 37000
=================================================================
Total params: 198945 (777.13 KB)
Trainable params: 198945 (777.13 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 83: early stopping
latent dim: 169 loss value is: 0.04557520151138306
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 185) 37185
dense_1 (Dense) (None, 177) 32922
dense_2 (Dense) (None, 170) 30260
dense_3 (Dense) (None, 177) 30267
dense_4 (Dense) (None, 185) 32930
dense_5 (Dense) (None, 200) 37200
=================================================================
Total params: 200764 (784.23 KB)
Trainable params: 200764 (784.23 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 46: early stopping
latent dim: 170 loss value is: 0.04695158451795578
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 185) 37185
dense_1 (Dense) (None, 178) 33108
dense_2 (Dense) (None, 171) 30609
dense_3 (Dense) (None, 178) 30616
dense_4 (Dense) (None, 185) 33115
dense_5 (Dense) (None, 200) 37200
=================================================================
Total params: 201833 (788.41 KB)
Trainable params: 201833 (788.41 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 75: early stopping
latent dim: 171 loss value is: 0.04330964386463165
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 186) 37386
dense_1 (Dense) (None, 179) 33473
dense_2 (Dense) (None, 172) 30960
dense_3 (Dense) (None, 179) 30967
dense_4 (Dense) (None, 186) 33480
dense_5 (Dense) (None, 200) 37400
=================================================================
Total params: 203666 (795.57 KB)
Trainable params: 203666 (795.57 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 48: early stopping
latent dim: 172 loss value is: 0.03677337244153023
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 186) 37386
dense_1 (Dense) (None, 179) 33473
dense_2 (Dense) (None, 173) 31140
dense_3 (Dense) (None, 179) 31146
dense_4 (Dense) (None, 186) 33480
dense_5 (Dense) (None, 200) 37400
=================================================================
Total params: 204025 (796.97 KB)
Trainable params: 204025 (796.97 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 52: early stopping
latent dim: 173 loss value is: 0.047755178064107895
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 187) 37587
dense_1 (Dense) (None, 180) 33840
dense_2 (Dense) (None, 174) 31494
dense_3 (Dense) (None, 180) 31500
dense_4 (Dense) (None, 187) 33847
dense_5 (Dense) (None, 200) 37600
=================================================================
Total params: 205868 (804.17 KB)
Trainable params: 205868 (804.17 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 71: early stopping
latent dim: 174 loss value is: 0.04531334713101387
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 187) 37587
dense_1 (Dense) (None, 181) 34028
dense_2 (Dense) (None, 175) 31850
dense_3 (Dense) (None, 181) 31856
dense_4 (Dense) (None, 187) 34034
dense_5 (Dense) (None, 200) 37600
=================================================================
Total params: 206955 (808.42 KB)
Trainable params: 206955 (808.42 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 61: early stopping
latent dim: 175 loss value is: 0.03927219286561012
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 188) 37788
dense_1 (Dense) (None, 182) 34398
dense_2 (Dense) (None, 176) 32208
dense_3 (Dense) (None, 182) 32214
dense_4 (Dense) (None, 188) 34404
dense_5 (Dense) (None, 200) 37800
=================================================================
Total params: 208812 (815.67 KB)
Trainable params: 208812 (815.67 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 46: early stopping
latent dim: 176 loss value is: 0.034685179591178894
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 188) 37788
dense_1 (Dense) (None, 182) 34398
dense_2 (Dense) (None, 177) 32391
dense_3 (Dense) (None, 182) 32396
dense_4 (Dense) (None, 188) 34404
dense_5 (Dense) (None, 200) 37800
=================================================================
Total params: 209177 (817.10 KB)
Trainable params: 209177 (817.10 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 54: early stopping
latent dim: 177 loss value is: 0.044353000819683075
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 189) 37989
dense_1 (Dense) (None, 183) 34770
dense_2 (Dense) (None, 178) 32752
dense_3 (Dense) (None, 183) 32757
dense_4 (Dense) (None, 189) 34776
dense_5 (Dense) (None, 200) 38000
=================================================================
Total params: 211044 (824.39 KB)
Trainable params: 211044 (824.39 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 87: early stopping
latent dim: 178 loss value is: 0.05755212903022766
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 189) 37989
dense_1 (Dense) (None, 184) 34960
dense_2 (Dense) (None, 179) 33115
dense_3 (Dense) (None, 184) 33120
dense_4 (Dense) (None, 189) 34965
dense_5 (Dense) (None, 200) 38000
=================================================================
Total params: 212149 (828.71 KB)
Trainable params: 212149 (828.71 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 51: early stopping
latent dim: 179 loss value is: 0.03674259036779404
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 190) 38190
dense_1 (Dense) (None, 185) 35335
dense_2 (Dense) (None, 180) 33480
dense_3 (Dense) (None, 185) 33485
dense_4 (Dense) (None, 190) 35340
dense_5 (Dense) (None, 200) 38200
=================================================================
Total params: 214030 (836.05 KB)
Trainable params: 214030 (836.05 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 42: early stopping
latent dim: 180 loss value is: 0.04764007404446602
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 190) 38190
dense_1 (Dense) (None, 185) 35335
dense_2 (Dense) (None, 181) 33666
dense_3 (Dense) (None, 185) 33670
dense_4 (Dense) (None, 190) 35340
dense_5 (Dense) (None, 200) 38200
=================================================================
Total params: 214401 (837.50 KB)
Trainable params: 214401 (837.50 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 53: early stopping
latent dim: 181 loss value is: 0.04117731377482414
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 191) 38391
dense_1 (Dense) (None, 186) 35712
dense_2 (Dense) (None, 182) 34034
dense_3 (Dense) (None, 186) 34038
dense_4 (Dense) (None, 191) 35717
dense_5 (Dense) (None, 200) 38400
=================================================================
Total params: 216292 (844.89 KB)
Trainable params: 216292 (844.89 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 46: early stopping
latent dim: 182 loss value is: 0.03711472824215889
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 191) 38391
dense_1 (Dense) (None, 187) 35904
dense_2 (Dense) (None, 183) 34404
dense_3 (Dense) (None, 187) 34408
dense_4 (Dense) (None, 191) 35908
dense_5 (Dense) (None, 200) 38400
=================================================================
Total params: 217415 (849.28 KB)
Trainable params: 217415 (849.28 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 69: early stopping
latent dim: 183 loss value is: 0.043860822916030884
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 192) 38592
dense_1 (Dense) (None, 188) 36284
dense_2 (Dense) (None, 184) 34776
dense_3 (Dense) (None, 188) 34780
dense_4 (Dense) (None, 192) 36288
dense_5 (Dense) (None, 200) 38600
=================================================================
Total params: 219320 (856.72 KB)
Trainable params: 219320 (856.72 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 62: early stopping
latent dim: 184 loss value is: 0.049317773431539536
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 192) 38592
dense_1 (Dense) (None, 188) 36284
dense_2 (Dense) (None, 185) 34965
dense_3 (Dense) (None, 188) 34968
dense_4 (Dense) (None, 192) 36288
dense_5 (Dense) (None, 200) 38600
=================================================================
Total params: 219697 (858.19 KB)
Trainable params: 219697 (858.19 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 65: early stopping
latent dim: 185 loss value is: 0.05139295011758804
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 193) 38793
dense_1 (Dense) (None, 189) 36666
dense_2 (Dense) (None, 186) 35340
dense_3 (Dense) (None, 189) 35343
dense_4 (Dense) (None, 193) 36670
dense_5 (Dense) (None, 200) 38800
=================================================================
Total params: 221612 (865.67 KB)
Trainable params: 221612 (865.67 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 45: early stopping
latent dim: 186 loss value is: 0.04698682948946953
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 193) 38793
dense_1 (Dense) (None, 190) 36860
dense_2 (Dense) (None, 187) 35717
dense_3 (Dense) (None, 190) 35720
dense_4 (Dense) (None, 193) 36863
dense_5 (Dense) (None, 200) 38800
=================================================================
Total params: 222753 (870.13 KB)
Trainable params: 222753 (870.13 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 91: early stopping
latent dim: 187 loss value is: 0.05039314925670624
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 194) 38994
dense_1 (Dense) (None, 191) 37245
dense_2 (Dense) (None, 188) 36096
dense_3 (Dense) (None, 191) 36099
dense_4 (Dense) (None, 194) 37248
dense_5 (Dense) (None, 200) 39000
=================================================================
Total params: 224682 (877.66 KB)
Trainable params: 224682 (877.66 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 86: early stopping
latent dim: 188 loss value is: 0.05140510946512222
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 194) 38994
dense_1 (Dense) (None, 191) 37245
dense_2 (Dense) (None, 189) 36288
dense_3 (Dense) (None, 191) 36290
dense_4 (Dense) (None, 194) 37248
dense_5 (Dense) (None, 200) 39000
=================================================================
Total params: 225065 (879.16 KB)
Trainable params: 225065 (879.16 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 45: early stopping
latent dim: 189 loss value is: 0.038218848407268524
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 195) 39195
dense_1 (Dense) (None, 192) 37632
dense_2 (Dense) (None, 190) 36670
dense_3 (Dense) (None, 192) 36672
dense_4 (Dense) (None, 195) 37635
dense_5 (Dense) (None, 200) 39200
=================================================================
Total params: 227004 (886.73 KB)
Trainable params: 227004 (886.73 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 72: early stopping
latent dim: 190 loss value is: 0.040986839681863785
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 195) 39195
dense_1 (Dense) (None, 193) 37828
dense_2 (Dense) (None, 191) 37054
dense_3 (Dense) (None, 193) 37056
dense_4 (Dense) (None, 195) 37830
dense_5 (Dense) (None, 200) 39200
=================================================================
Total params: 228163 (891.26 KB)
Trainable params: 228163 (891.26 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 43: early stopping
latent dim: 191 loss value is: 0.04388617351651192
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 196) 39396
dense_1 (Dense) (None, 194) 38218
dense_2 (Dense) (None, 192) 37440
dense_3 (Dense) (None, 194) 37442
dense_4 (Dense) (None, 196) 38220
dense_5 (Dense) (None, 200) 39400
=================================================================
Total params: 230116 (898.89 KB)
Trainable params: 230116 (898.89 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 64: early stopping
latent dim: 192 loss value is: 0.04522009566426277
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 196) 39396
dense_1 (Dense) (None, 194) 38218
dense_2 (Dense) (None, 193) 37635
dense_3 (Dense) (None, 194) 37636
dense_4 (Dense) (None, 196) 38220
dense_5 (Dense) (None, 200) 39400
=================================================================
Total params: 230505 (900.41 KB)
Trainable params: 230505 (900.41 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 66: early stopping
latent dim: 193 loss value is: 0.053198155015707016
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 197) 39597
dense_1 (Dense) (None, 195) 38610
dense_2 (Dense) (None, 194) 38024
dense_3 (Dense) (None, 195) 38025
dense_4 (Dense) (None, 197) 38612
dense_5 (Dense) (None, 200) 39600
=================================================================
Total params: 232468 (908.08 KB)
Trainable params: 232468 (908.08 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 53: early stopping
latent dim: 194 loss value is: 0.03060125559568405
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 197) 39597
dense_1 (Dense) (None, 196) 38808
dense_2 (Dense) (None, 195) 38415
dense_3 (Dense) (None, 196) 38416
dense_4 (Dense) (None, 197) 38809
dense_5 (Dense) (None, 200) 39600
=================================================================
Total params: 233645 (912.68 KB)
Trainable params: 233645 (912.68 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 70: early stopping
latent dim: 195 loss value is: 0.043699778616428375
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 198) 39798
dense_1 (Dense) (None, 197) 39203
dense_2 (Dense) (None, 196) 38808
dense_3 (Dense) (None, 197) 38809
dense_4 (Dense) (None, 198) 39204
dense_5 (Dense) (None, 200) 39800
=================================================================
Total params: 235622 (920.40 KB)
Trainable params: 235622 (920.40 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 51: early stopping
latent dim: 196 loss value is: 0.04921839013695717
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 198) 39798
dense_1 (Dense) (None, 197) 39203
dense_2 (Dense) (None, 197) 39006
dense_3 (Dense) (None, 197) 39006
dense_4 (Dense) (None, 198) 39204
dense_5 (Dense) (None, 200) 39800
=================================================================
Total params: 236017 (921.94 KB)
Trainable params: 236017 (921.94 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 98: early stopping
latent dim: 197 loss value is: 0.05170490965247154
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 199) 39999
dense_1 (Dense) (None, 198) 39600
dense_2 (Dense) (None, 198) 39402
dense_3 (Dense) (None, 198) 39402
dense_4 (Dense) (None, 199) 39601
dense_5 (Dense) (None, 200) 40000
=================================================================
Total params: 238004 (929.70 KB)
Trainable params: 238004 (929.70 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 75: early stopping
latent dim: 198 loss value is: 0.05717887356877327
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 200)] 0
dense (Dense) (None, 199) 39999
dense_1 (Dense) (None, 199) 39800
dense_2 (Dense) (None, 199) 39800
dense_3 (Dense) (None, 199) 39800
dense_4 (Dense) (None, 199) 39800
dense_5 (Dense) (None, 200) 40000
=================================================================
Total params: 239199 (934.37 KB)
Trainable params: 239199 (934.37 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 45: early stopping
latent dim: 199 loss value is: 0.04247467219829559
--------------------------------------------------------------------------- FileNotFoundError Traceback (most recent call last) /home/moh/Documents/PhD/BLEWBAN_Dataset/Examples/auto_encoder.ipynb Cell 2 line 2 <a href='vscode-notebook-cell:/home/moh/Documents/PhD/BLEWBAN_Dataset/Examples/auto_encoder.ipynb#W1sZmlsZQ%3D%3D?line=198'>199</a> plt.ylabel('Best loss') <a href='vscode-notebook-cell:/home/moh/Documents/PhD/BLEWBAN_Dataset/Examples/auto_encoder.ipynb#W1sZmlsZQ%3D%3D?line=199'>200</a> plt.title('dataset: onBody static left') --> <a href='vscode-notebook-cell:/home/moh/Documents/PhD/BLEWBAN_Dataset/Examples/auto_encoder.ipynb#W1sZmlsZQ%3D%3D?line=200'>201</a> plt.savefig('res/'+"onBody static left"+'.png') <a href='vscode-notebook-cell:/home/moh/Documents/PhD/BLEWBAN_Dataset/Examples/auto_encoder.ipynb#W1sZmlsZQ%3D%3D?line=201'>202</a> plt.show() <a href='vscode-notebook-cell:/home/moh/Documents/PhD/BLEWBAN_Dataset/Examples/auto_encoder.ipynb#W1sZmlsZQ%3D%3D?line=202'>203</a> plt.close() File ~/.local/lib/python3.10/site-packages/matplotlib/pyplot.py:954, in savefig(*args, **kwargs) 951 @_copy_docstring_and_deprecators(Figure.savefig) 952 def savefig(*args, **kwargs): 953 fig = gcf() --> 954 res = fig.savefig(*args, **kwargs) 955 fig.canvas.draw_idle() # Need this if 'transparent=True', to reset colors. 956 return res File ~/.local/lib/python3.10/site-packages/matplotlib/figure.py:3274, in Figure.savefig(self, fname, transparent, **kwargs) 3270 for ax in self.axes: 3271 stack.enter_context( 3272 ax.patch._cm_set(facecolor='none', edgecolor='none')) -> 3274 self.canvas.print_figure(fname, **kwargs) File ~/.local/lib/python3.10/site-packages/matplotlib/backend_bases.py:2338, in FigureCanvasBase.print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, pad_inches, bbox_extra_artists, backend, **kwargs) 2334 try: 2335 # _get_renderer may change the figure dpi (as vector formats 2336 # force the figure dpi to 72), so we need to set it again here. 2337 with cbook._setattr_cm(self.figure, dpi=dpi): -> 2338 result = print_method( 2339 filename, 2340 facecolor=facecolor, 2341 edgecolor=edgecolor, 2342 orientation=orientation, 2343 bbox_inches_restore=_bbox_inches_restore, 2344 **kwargs) 2345 finally: 2346 if bbox_inches and restore_bbox: File ~/.local/lib/python3.10/site-packages/matplotlib/backend_bases.py:2204, in FigureCanvasBase._switch_canvas_and_return_print_method.<locals>.<lambda>(*args, **kwargs) 2200 optional_kws = { # Passed by print_figure for other renderers. 2201 "dpi", "facecolor", "edgecolor", "orientation", 2202 "bbox_inches_restore"} 2203 skip = optional_kws - {*inspect.signature(meth).parameters} -> 2204 print_method = functools.wraps(meth)(lambda *args, **kwargs: meth( 2205 *args, **{k: v for k, v in kwargs.items() if k not in skip})) 2206 else: # Let third-parties do as they see fit. 2207 print_method = meth File ~/.local/lib/python3.10/site-packages/matplotlib/_api/deprecation.py:410, in delete_parameter.<locals>.wrapper(*inner_args, **inner_kwargs) 400 deprecation_addendum = ( 401 f"If any parameter follows {name!r}, they should be passed as " 402 f"keyword, not positionally.") 403 warn_deprecated( 404 since, 405 name=repr(name), (...) 408 else deprecation_addendum, 409 **kwargs) --> 410 return func(*inner_args, **inner_kwargs) File ~/.local/lib/python3.10/site-packages/matplotlib/backends/backend_agg.py:517, in FigureCanvasAgg.print_png(self, filename_or_obj, metadata, pil_kwargs, *args) 468 @_api.delete_parameter("3.5", "args") 469 def print_png(self, filename_or_obj, *args, 470 metadata=None, pil_kwargs=None): 471 """ 472 Write the figure to a PNG file. 473 (...) 515 *metadata*, including the default 'Software' key. 516 """ --> 517 self._print_pil(filename_or_obj, "png", pil_kwargs, metadata) File ~/.local/lib/python3.10/site-packages/matplotlib/backends/backend_agg.py:464, in FigureCanvasAgg._print_pil(self, filename_or_obj, fmt, pil_kwargs, metadata) 459 """ 460 Draw the canvas, then save it using `.image.imsave` (to which 461 *pil_kwargs* and *metadata* are forwarded). 462 """ 463 FigureCanvasAgg.draw(self) --> 464 mpl.image.imsave( 465 filename_or_obj, self.buffer_rgba(), format=fmt, origin="upper", 466 dpi=self.figure.dpi, metadata=metadata, pil_kwargs=pil_kwargs) File ~/.local/lib/python3.10/site-packages/matplotlib/image.py:1664, in imsave(fname, arr, vmin, vmax, cmap, format, origin, dpi, metadata, pil_kwargs) 1662 pil_kwargs.setdefault("format", format) 1663 pil_kwargs.setdefault("dpi", (dpi, dpi)) -> 1664 image.save(fname, **pil_kwargs) File /usr/lib/python3/dist-packages/PIL/Image.py:2317, in Image.save(self, fp, format, **params) 2315 fp = builtins.open(filename, "r+b") 2316 else: -> 2317 fp = builtins.open(filename, "w+b") 2319 try: 2320 save_handler(self, fp, filename) FileNotFoundError: [Errno 2] No such file or directory: 'res/onBody static left.png'
len(df['I'][0])
import numpy as np
import matplotlib.pyplot as plt
row =np.random.rand(10)
filename = files[3]
print(filename)
f = open(dataDir+filename, 'rb')
data_tuples = pickle.load(f)
f.close()
df = pd.DataFrame(data_tuples, columns=['predictor', 'label'])
def fft_normalized(row):
temp = np.fft.fft(row)[0:len(row)//2 + 1]
amp = normalized(np.abs(temp))
filtering = amp > np.max(amp)*0.05
angle = normalized(np.angle(temp))
angle = angle[filtering]
amp = amp[filtering]
return np.concatenate([amp,angle])
df['normalized'] = df['predictor'].apply(lambda x: fft_normalized(x))
tf.convert_to_tensor( df['normalized'].to_list())
# best_losses = dict(sorted(best_losses.items()))
# lossDF = pd.DataFrame(best_losses.values(),index=best_losses.keys())
def read_loss(file :str | os.DirEntry):
if type(file) is str:
if file.endswith(".csv"):
lossDF = pd.read_csv(file,index_col=0)
return lossDF
else:
if file.name.endswith(".csv"):
lossDF = pd.read_csv(file.path,index_col=0)
return lossDF
def plot_loss(file):
read_loss(file)
lossDF.plot()
plt.xlabel('Latent dimension')
plt.ylabel('Best loss')
plt.title('dataset: '+file.name)
plt.savefig('res/'+file.name+'.png')
plt.show()
plt.close()
# for file in os.scandir('res/RAE-_l2-0.001/'):
df = read_loss("loss_dataset1.pkl.csv")
import scipy.signal as signal
def smooth(x,window_len=11,window='hanning'):
if x.ndim != 1:
raise ValueError("smooth only accepts 1 dimension arrays.")
if x.size < window_len:
raise ValueError("Input vector needs to be bigger than window size.")
if window_len<3:
return x
if not window in ['flat', 'hanning', 'hamming', 'bartlett', 'blackman']:
raise ValueError(f"Window is on of '{window}'")
s=np.r_[x[window_len-1:0:-1],x,x[-2:-window_len-1:-1]]
#print(len(s))
if window == 'flat': #moving average
w=np.ones(window_len,'d')
else:
w=eval(f'np.{window}({window_len})')
y=np.convolve(w/w.sum(),s,mode='valid')
return y
plt.plot(smooth(df['0'].to_numpy(),window_len=5, window='hamming'))